Skylab EREP Investigations Summary

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SKYLAB

Investigations SummaryNationa Aeronauticsand Space Administration

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Skylab EREP Investigations Summary





N A S A SP-399

SkylabEREPInvestigations

Summary

Prepared byN A S A L y n d o n B . Johnson Space Center

Scientific an d Technical Information OfficeN A T I O N A L A E R O N A U T I C S A N D S PA C E A D M I N I S T R A T I O NWashington, D.C.

1978



M any individuals of the scient ific com mun ity and the NA SA Lynd on B. Johnson Space C enter (JSC)

provided imm easura ble ass is tance in preparat ion of this report , and their support is gratefullyackno wled ged. Sp ecial recognition is given to W illard J. Pierson, C ity Un iversity of New Yo rk, w hoserved as senior edi tor , and to V ictor L. Et tredge and Verl R. W ilmarth of JSC for their dedicat ionand many cont r ibut ions in comple t ing th i s summary volum e.

Library of Congress Cataloging in P u b l i c a t i o n Da t a

L y n d o n B. Johnson Space Center.

S ky l a b EREP investigations s u m m a r y .

(NASA SP; 399)

Supt. of Docs, no . : NAS 1.21:399

1. Remote sensing. 2. S ky l a b Program. I. Title. II. Series:

Uni ted States. National Aeronautics and Space Admin i s t ra t ion . NASA

SP; 399.

G70.4.L94 1978 621.36'7 78-606049

Fo r sale by (he Superintendent of Documents

U.S. Government Printing Office, Wash ington, D.C. 20402

Stock No. 033-000-00741-8



Foreword

O N F E B R U A R Y 8, 1974, the final S kyl ab mission ended with the sp lashdown of the S kyl ab 4 astro -n au ts in the Paci f ic Ocean. Th e scient i f i c an d tech n o lo g ica l ach iev em en ts f ro m th e S kyl ab m a n n e dsp ace p ro g ram a r e n u mero u s an d in c lu d e n ew kn o wled g e o f solar p h en o m en a , o f man ' s ca pa b i l i t y

fo r lo n g -d u ra t io n sp ace f l igh t , and of the Ear th through the sophis t icated sensors th a t co mp r ise th eEar th Resources Exp er imen t Packag e (EREP) .

Th e E R EP acqu i r ed th o u san d s o f p h o to g rap h s an d sev era l mi les o f mag n e t ic tap e in wh ich Ear thsurface features and phenomena of selected reg ions on f ive co n t in en ts an d two ma jo r oceans wererecorded . Some data showed p lumes of erupting volcanoes , c i rcu lar p a t te rn s o f a ma jo r h u r r ican e ,contras t ing co lors of ocean eddies and upwe ll ings , and grow th patte rns of me tropoli ta n com plexes ,wh ereas o th e r d a ta co n ta in ed in f o rmat io n o n vegetat ion patterns , geological ter ra in , landforms,snowfields , and icef ields . Investigators in the U nited S tates and 28 o ther countr ies hav e analyzed

these data , and the resu l ts of their investigations are summ arized in the d iscip l ine sections here in .The success of E R E P was due to the dedication and ta len ts of man y p eo p le in N A S A , i n d u s t r y ,and t he sc ien t i f ic co mmu n i ty . I t r emain s , h o wev er , for the Earth scientists, design engineers,

resource managers , and data analysts to capita l ize on the EREP r esu l t s to i m p r o v e our f u tu r ec ap ab i l i t y to mo n i to r th e Ear th ' s d yn amic sys tems f rom space and to effectively use and conserveour natural resources .

C H R I S T O P H E R C . KRAFT, JR .Director, Lyndon B. Johnson Space Center



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Preface

TH E O V E R A L L P U R P O S E O F THE Ear th Resources E x p e r i m e n t P a c k ag e ( E R E P ) was to test the use ofsensors that operated in the v is ible , inf rare d , and m icro wa ve por t ions of the electromagneticsp ec t ru m to m o n i t o r a n d study Ear th resources . Dur ing th e three Skylab man ned m iss ions , th e astro-n au ts o p era ted th e EREP sensors acco rd in g to in s t ru c t io n s f ro m th e ER EP p la n n in g team in th eMission Contro l Center at the N A S A L y n d o n B . Johnson Space Center . In th is ro le , th e cr ewmenwere member s of the scien tif ic teams that perform ed Ea r th resources exp er iments . A s a m e m b e r o fth e S k y l a b 3 c r e w , I kn o w th a t th e p a r t w e p layed in the col lect ion of these data fo r sc ien t i f ic s tu d y ofth e E a r t h w as bo th f a sc in a t in g a n d reward in g .

W h e n th e E a r t h is v iewed f rom an a l t i t u d e of 435 km (235 n. mi . ) , th e m u l t i t u d e of features repre-sented in many co lors and tones a re in d ica t iv e o f th e co mp lex i ty o f processes and systems that aremanifes ted on the Ear th 's surface. To unders tand these p h en o men a r equ i r es a synoptic v iew f romspace and sensors cap ab le of obtain ing h igh-reso lu tion data in the ap p ro p r ia te p a r t s of theelectromagnetic spectrum. In rev iewing the resu l ts of the EREP investigations summarized in th isr ep o r t , it is ev ident that major s teps have been taken in developing a cap ab i l i ty to conduct Ear thscience from space.

This docum ent summ arizes the analy tica l resu l ts of 139 investigators who used EREP d a ta intheir investigation o f p ro b lems in the areas o f agr icu l ture , range, an d forestry; land use and car togra-

phy; geology and hydro logy; and oceans and atmosphere, and in their development of data analysistech n iqu es . In fu ture space exploration , th e results of E R E P wi l l serve as a milestone for thedevelopment of an applicat ions research technology for the s tudy of Ear th resources .

O W E N K . G A R R I O T TScience Pilot, Skylab 3

VII






ContentsPage

1. I N T R O D U C T I O N 1

2. L A N D U S E A N D C A R T O G R A P H Y 7Roger M . Hoffer, R. E. Joosten, R. G. Davis, and F. R. Brumbaugh

3 . A G R I C U L T U R E , R A N G E , A N D F O R E S T R Y 7 9Robert N . Colwell, F. Philip W eber, an d Ryborn R. Kirby

4 . GEOLOGY AND HYDROLOGY 119Richard A. Hoppin, Duwayne M. Anderson, Robert K. Stewart, David L. Amsbury , Von R. Frierson,

A. Victor Mazade, an d Martin L . Miller

5. O C E A N S A N D A T M O S P H E R E 1 8 9W illard J. Pierson, W illiam E. Marian, Zack H, Byrns, an d W illiam R. Johnson

6 . D A T A A N A L Y S I S T E C H N I Q U E S 25 7Fabian C. Polcyn, Kenneth R. Piech, Allan Shapiro, Larry B. York, an d Andrew E. Potter

A P P E N D I X A — E R E P S E N S O R S Y S T E M S 3 43Roy L. Eason

A P P E N D I X B — S K Y L A B E R E P P R I N C I P A L I N V E S T IG A T O R S 3 6 3

A P P E N D I X C — P H O T O G R A P H I N D E X 3 7 1

A P P E N D I X D — P R I N C I P L E S O F P H O T O G R A P H I C A N D 3 7 7D I G IT A L D A T A A N A L Y S I S

Fund a me nta l s o f Pho togra ph ic In te rp re ta t ion 377Robert N. Colwell

Digi ta l A n a lys i s Techn iq ues 38 0Roger M . Hoffer and A. Victor Mazade

A P P E N D I X E — S T A N D A R D W E A T H E R S Y M B O LS 3 8 5

IX



1Introduction

R i M O T E S E N S I N G of the Ear th f rom orb i t a l a l t i tudeswas recognized in the mid-1960's as a po ten t i a l

t e chn ique fo r o b t a i n i n g i n f o r m a t i o n i m p o r t a n t for theeffective use and conservat ion of natural resources.These studies began when th e Tiros satel l i tes (1960)prov ided m a n ' s f i rst synopt ic view of the Earth ' sweather systems. The manned Gemini and Apol lo Pro-

grams (1965-72) led to further consideration of space-age remote sensing fo r s tudy of the Ear th . The Ear thResources Technology Sate l l i te , now designated Land-sat, provided repeti t ive multispectral scanner data inth e visib le and infrared regions of the e lect romagnet icspect rum for large areas of the Earth . The Landsatseries consisted of Landsat-1 launched in 1972 andLandsat -2 in 1975. Skyla b , the largest manne d space sta-tion ever placed in low Ear th o rb i t , w as l aunched in1973 and carr ied into space the Ea rth Resources Ex per i -men t Package (EREP) , w h i c h was designed to view theEar th w i th sensors that recorded data in the visib le , in -frared, and microwave spect ral regions. Thus, EREPbecame another s tep in space exp lorat ion by test ing the

use of high- resolut ion camera systems wi th film r e t u r nc a p a b i l i t y , n a r r o w f r e q u e n c y b a n d w i d t h s c a n n e rsystems in the visib le through th erma l - infrared spectralregions, and the init ial use of active an d passivemicrowave systems in Ear th resource surveys. A sig-nif icant feature of ER EP was the use of man to operateth e sensors in a laboratory fashion. Skylab object ivesalso inc luded scientific observations of the Sun, thestars , and near-Earth space ; mater ial s research andmanufactur ing in a weightless environment ; observa-tion of l iving-organism functions in a near-zero-g en-v i r o n m e n t ; and deve l opment of techniques fo r long-d u ra t io n manned-space - f l i gh t ope ra t ions .

The Skylab spacecraf t was launched eastwardly on a50° az imuth f rom the N AS A John F . Kennedy SpaceCen ter, Florida , on Ma y 14, 1973, into a near- circu larorb i t at an a l t i t ude of 435 km above th e Ear th . It orbitedt h e E a r t h e v e r y 9 3 m i n u t e s a n d r e p e a t e d t h eg ro u n d t r ack every 5 days. The launch a zim uth incl inedth e orbi ta l p l ane 50° wi th respect to the Equator and

l imited observat ions of the Earth to lat i tudes be tween50° N and 50° S (fig. 1-1).

Skylab w as occupied by three three-man crews dur-ing th e period May 25, 1973, to February 8, 1974, for atotal of 17 1 days in space (table 1-1). At the end of theS kyl ab 4 mission, the vehic le was deact ivated and re -mains today in a near-c i rcular orbi t about th e E a r t h .

The E R E P w as designed to exp l o re the use of thewidest possib le por t ion of the e lec t romagnet ic s pect ru mfo r Ea rth resource inve stiga tions . It consisted of twopho tograph i c and four electronic sensor systems (tablel -I I ) that s imul taneously permit ted remote sensing ofth e E a r t h ' s s u r f a c e in the v i s i b l e , i n f r a r e d , a n dmicrowave regions of the spectrum (fig. 1-2). The

ground coverage for each sensor is shown in figure 1-3.The EREP sensor systems and the i r data products a redescr ibed in appendix A.

The EREP Program began in December 1970 wi ththe announcement by NASA that data col lec ted by theE R E P w o u l d be m a d e avai lable to qualified investiga-tors fo r Earth resource investigations. From th eresponse to t h i s announcement , NASA selected 164tasks to be performe d by 148 Princip al Invest igatorsrepresenting academic, governmental , and industrialfirms in th e United States and 19 other countries. (A listof the Pr incipal Invest igators i s contained in appendixB .) These invest igators analyzed EREP data and ap-



90 100 120 140 160 180 160 140 120 100

E-—I—-W

Longitude, deg

F I G U RE 1-1.—Sky lab ground coverage .

20

W -

S190A

S190B

SI 91

S192

S193

S194

i

++HBlack-and-white f i lm

)*MMM Color- in frared f i lm -

MMM* Color film -1 band

IMMMM Color, co lor- in frarec1 band

**WHHWM M

s ^--Visible spectrum

1 1 l-.::i III 1 III

-4 bands

1 band

, or black-and-white film

^ ^ ) 2 bands

-

1 2 detectors

( 13 bands1

1 1 3 detectors

1

i i i 1 1 1 1 1 in i tv i ir-

.2 .4 .6 .8 1 2 4 6 8 10 16 ~ 2 . 2 c m 2 1 c mW a v e l e n g t h , (im

F I G U RE 1-2.—Wavelength sensitivity of E a r t h -v i e w i ng S ky l a b

F I G U RE 1-3.—The ground a rea coverage provided by E R E P sensors

(S-73-005-S).

2 S K Y L A B ER E P I N V E ST IG A T IO N S S U M M A R Y



T A B L E 1-1.—Sky ab Mission Summary

Misson Crevmembers Launch date Splashdown date Duration,

days

aS k y l a b 1 None M ay 1 4 , 1 9 7 3 N ot appl icable

( N A )

N A

Integrat ion of the data requirements for each in-vestigative area resulted in a mission requirementsdocu ment th at was used by the E R E P Team to plan, inthe M iss ion Cont ro l Cente r a t t he N AS A Lyn don B .John son Space Center (JS C), each E R E P data pass on adai ly basis during the three m anned miss ions . Each

E R E P pass w as planned within miss ion constra ints toS k y l a b 2 Charles Conrad, J r . , May 2 5 , 1973 June 22 , 1973 28

commander ( C D R )

Joseph P. K e r w i n ,

science pi lo t (SPT)

Paul J. W e i tz ,

pi lo t (PLT)

S k y l a b 3 A lan L . B ean , J u l y 28 , 1973 Sept. 25 , 1973 59

C D R

Owen K . G a r r i o t t ,

SPT

J ack R . Lousma,

PL T

S ky l ab4 Gerald P. Carr, N o v . 16 , 1973 Feb. 8, 1974 84

C D RE d w a r d G . Gibson,

SPTW i l li a m R Pogue,

PL T

aLaunch of Skylab orbital workshop. The vehicle was operated unm anned between

manned missions.

plied their results to nine major investigative areas thatincluded agricu l ture , range, and fores try; geologic ap-pl icat ions; con tinen tal water resources; oceanograph icand atm osp heric in vestigatio ns; coastal zones, shoals,

a n d b a y s ; r e m o t e - s e ns i ng t e c hn i q ue de ve l opm e n t ;regional planning and development; and cartography.W i t h i n each of these areas, studies of specific featuresand phenom ena were conduc ted using ERE P, Landsa t,aircraft, and ground measurement data .

Each invest igat ion required specif ic EREP data ,which were defined by the Principal Invest igators andused to preplan th e operation of the EREP dur ing th emiss ion . D epending on the scope of the inves t igat ions ,the data requirements ranged from a series of photo-graphs obtained by the S190A an d S190B camerasystems to compu te r -compa t ib l e t apes and color-com-posite images derived from the SI 92 mu lt ispectra l scan-ner .

Th emicrowave sensors

(SI 93 andS194) recorded

data on magnet ic tape fo r processing an d ana lyz ing wi thcomputers .

uuiam nit: 3|*«i«uiv uaia ut ua uj aa many uivcougaiuva

as possible. Because most in vestig ation s required d ataobtained w i th m i n i m u m c l oud c ove r , th e Space Fl ightMeteorological Group of the Nat ion al W eather Serviceat JSC was an essent ia l part of the o perat ion pla nn ingteam. Before each E RE P pass, a deta iled t im e schedulefor operat ion of each sensor was up l ink ed to the crew.

T A B L E l-ll— E RE P Sensors

Sensor

Mult ispec t ral Photo-

gr ap h ic Camera

system (S190A)

Ear th T er r a i n

Camera (S190B)

Infrared Spec-

trometer (S191)a

Mul t i s p ec t r a l

Scanner (S192)a

M i c r o w a v e systems3

K - ban d : M i c r o w av e

R a d i o m e t e r /

Scatterometer0 an d

Al t i me t e r 0 (S193)

L - b a n d : L- Ban d

Rad iom ete r1" (S194)

Description Wavelength

range.u,m

Six 70-mm bore- 0.4 to 0.9

sighted cameras;

color , b l ac k - an d -

w h i t e , color-

i n f r a r ed , a n d

b l a c k - a n d - w h i t e

inf rared f i lms

Sing le 127-mm cam era; 0 .4 to 0.88

co lor , black-and-

w h i t e , an d color-

i n f r a r e d f i l m s

Fil ter -wheel spectrom- 0.4 to 2.5;

eter; 1-sec scan rate; 6.6 to 16.0

1 6 - mm c a m e r a t h a trecords Ear th scenes;

crew po in ted

13-channel opt ical - 0.4 to 2.35;

mec h an i c a l scanner 10.2 to 12.5

3-sensor fac i l i ty;

uses s ingle 1.1 -m,

p o i n t ab l e , p a r a -

bolic a n t e n n a

Single sensor;

f i x e d a n t e n n a

Frequency

range.GHz

—

—

13.8 to 14.0

1.4to 1.427

aDa t a recorded on magnetic tape.

Passive sensors.

Active sensors.

I N T R O D U C T I O N 3



To conduc t a conven t iona l EREP pass, th e creworiented Skylab to poin t the E R EP sensors no rma l (per-p e n d i c u l a r ) to the Earth ' s surface . In t h i s pos i t i on , th eZ-axis of the spacecraf t w as al ined wi th local ver t ical( Z - L V ) . W ith the exception of a few passes, a l l EREPdata passes were accompl i shed in a Z - L V p o s i t io n .

During the 171 days of manned Sky l ab ope ra t ion ,110 E R E P passes were completed (table l -III) . These

passes resulted in more than 35 000 frames of photogra-phy and 72 725 m (238 600 ft) of magnetic tape.

Skylab orbi tal groundtracks permit ted th e E R E Psensors to view th e Uni ted States; th e con t inen t s ofSouth America, Africa , and Aust ral ia; the southern par tof Europe and Asia ; and large areas of the At l an t i c andPacific Oceans ( fig. 1-1). Each m ann ed m ission resultedin an abundance of Ear th resource data, some of whichis uniqu e . Skylab missions were f lown d u r i n g th e sum-mer , f a l l , a n d w i n t e r m o n t h s i n t h e N o r t h e r nHemisphe re , and some repetit ive data were collectedd u r in g each season fo r selected test sites. Mission con-

s t r a in t s required that dur ing th e Sky l ab 2 mission, onlydescending (north to south) passes could be performed;d u r in g th e S kyl ab 3 and 4 missions, both descendingand ascending (south to n o r t h ) passes were conducted.In general , the data collection period for each passranged from 15 to 25 m i n u t e s an d covered agro und trac k distan ce of 6482 to 11 112 km (3500 to6000 n. mi.) .

D u r i n g Skylab 2 , EREP data were col lec ted on de-scending ground tracks over the U ni ted States , the Gulfof Mexico, the Caribbean Sea, and northern regions ofSouth America. About midway of this mission, an in-tense hurr icane (Hurr icane Ava) , located approx-ima te ly 1000 km (550 n. mi.) southwest of Acapulco,Mexico , was v i s ib l e t o t he EREP sensors , and un ique

T A B L E l-III.— EREPD a t a Summary

Mission

Skylab 2

Skylab 3

Skylab 4

E R E P passes

13

48

49

Photographs Magnetic tape,

(frames) m (ft)

5275 13716 (45000)

13429 2 8 5 2 9 (93600)

17000 30480 (100000)

p h o t o g r a p h s and microw ave data were obtained concur-r en t l y with U.S. A ir Force reconnaissance aircraft

fl ights. Th e Skylab 3 c rewmen re tu rned l a rge quan t i t i e sof pho tograp hic and m agnet ic tape data obtained on as-cen d in g and descending groun dtra cks over the Uni tedStates and 28 coun t r i e s in Cent ra l and South America,Europe , western Africa , Asia, and Au stral ia . Single data

passes were accompl ished over Japan and adjacentocean, Israe l , Ethiopia, Malaysia, Aust ral ia , an d New

Zealand. During th e Skylab 3 mission, specific featuressensed by t he ER EP inc l uded t he ac tive vo l cano M ountE tna , Sicily; th e drought regions of M a l i and ad jacen tcountr ies ; and t ropical s torm Christ ine in the At l an t i cOcean northeast of the coast of Venezuela.

Skylab 4 was f lown d u r i n g th e win te r months in theNor the rn Hemisphe re ; t he re fo re , l igh t ing cond i t i onswere n ot favorable fo r ER EP da t a co l le c t ion in Decem-ber 1973. Nevertheless, th e 84-day mission resulted insuccessful E R E P passes over portions of the worldgeneral ly covered during th e Sky l ab 3 mission. In add i -t ion, some unique data collection passes were com-ple ted inc lud ing predaw n and near- local -noon sensing

4 S K Y L A B E R E P I N V ES T IG A T IO N S S U M M A R Y



of selected areas in California for test ing the thermal-m a p p i n g capabil i ty of the S192, ov erflig ht of the largestextratropical cyclone in the North Atlantic in a decade,and a 360° S192 altimeter data pass that began atlongitude 39° W and ended at longitude 61° W tomeasure th e configurat ion of the Earth. Photographic

data in both obl ique (solar inert ial) and Z-LV modeswere obtained by the Skylab 3 and 4 crewmen overParaguay to test the uti l i ty of space photography intopographic mapping of remote regions.

Th e vast quanti ty of EREP photographic , scanner ,spectrometric , and microwave data re turned from the171 days of mann ed Skylab operat ions at test to theoperat ional success of the sensor systems. To operateth e sensor systems, th e astronauts had to perform aseries of tasks that included replacing film cassettes fo rthe S190A and S190B cameras, manual ly pointing thetelescope and operat ing th e S191 spectrometer, and alin-in g th e S192 scanner detector system to opt imize th esignal received du ring data collection. Late in the Skylab4 mission, the astronauts replaced the SI 92 channel 13thermal detector with a more sensitive detector andthermal data were collected over sites in southernCalifornia. The complex S193 microwave system oper-a t e d s a t i s fac t o r i l y du r i ng t he Sk y l ab 2 mi s s i on ;however , th e scan motion compensator malfunctionedduring the S kylab 3 mission. The Skylab 4 crewreestabl ished the anten na capabil i ty in the rol l direction(normal to the groundt rack) , but the pi tch mot ion w asno t repaired. The loss of the S193 antenna came in thelatter part of the Skylab 4 mission and resulted in

d e g r a d a t i o n of the d a t a . T h e S 1 9 4 m i c r o w a v eradiometer operated w itho ut malfunctions for the threemanned missions. In summary , EREP data col lec t ionprovided, for each Principal Invest igator (PI) , a com-

prehens ive set of photographs and magnetic tapes con-taining data in the visible through microwave spectralregions over a wide variety of scenes, features, andphenomena of the Earth's surface.

Upon completion of each manned mission, theER EP data were re turned fo r processing at JSC accord-in g to the requirements of indiv idua l invest igators. Thephotographs were distributed soon after comple t ion ofeach mission, but the complex i ty of the electronic dataresul ted in delays in the distribution of such data to thePi 's . Information on geographic areas for which datawere obtained by the EREP sensors is contained in theSkylab Earth Resources Data Catalog (ref. 1-1). The PIreports on analysis of the ER EP da t a can be obtainedfrom the National Space Science Data Center, NASAGoddard Space Fl ight Center, Greenbel t , Maryland20771.

The purpose of th is summary volume is to describeth e significant accomplishments of the ER EP da t aanalysis program in the areas of agricul ture , range, andfo r e s t ry ; geology a n d h y d r o l o g y ; o c e a n s and a t -mosphere; land use and car tography; an d data analysistechniques. Th e results presented in this report indicateth e manner in which space remote sensing is applied inEarth resource surveys today, th e needs of future spaceremote-sensing systems, and some potential appl ica-t ions of space d ata in conservation and uti l izat ion ofnatura l resources.

R EF ER EN C E

1-1. Skylab Earth Resou rces Da t a Ca t a l o g . N A SA Rep . JS C

09016, U.S. G o v e r n m e n t Print ing Office (stock no . 3300-

00586) (W ashington , D.C.), 1974.

I N T R O D U C T I O N 5






Land U se and CartographyR O G E R M. HOFFER.^R. E. JOOSTEN? R. G. DA yis,c

A N D F . R . B R U M B A U G H

A J I N C R E A S I N G P O P U L A T I O N and a growing aware-

ness of the f ini te natu re of U.S. natural resources

hav e created a d em a n d fo r more ef fec t ive l an d use p l a n -n ing and m a p p i n g p r o g r a m s . In the past decade, N a-t ional , State, an d local legislation has been enac ted fo rbet ter management of land and resources. Conf l ic ts fo ral ternate uses of the l and are ev i d en t ev e r y w h e r e : u r b a n

ex p a n s i o n decreases land available for agr icul ture; in-crease in s t r ip min ing r a ises env i ronm enta l concerns;fo res t t imber p roduc t ion competes with r ec rea t iona lneeds; and commerc ia l developments can adversely

affect r es iden t ia l communi t ies . In examin ing theses i tua t ions , effect ive l and use p la nn in g r equ i r es accura teup- to -da te in fo rmat ion concern ing th e c u r r en t use ofth e l and and the po ten t ia l c ap ab i l i t ies of the land. Such

informat ion i s of ten very dif f icu l t to o b t a i n , par t i cu l a r l yif large geographic regions are involved.

In discussing th e app l ica t ion of the Ear th ResourcesE x p e r i m en t Pa c k a g e (E R E P) d a t a to l and use and car-t o g r a p h y , it is i m p o r t a n t to d is t ingu ish be tween these

tw o disc ipl ine ac t ivi t ies . Th e l and use app l ica t ion in -cludes natural resource inventor ies and p lann ing r e la -t ionsh ips ; th e car tograph ic app l ica t ion is concerned

wi th mapping ac t ivi t ies . Therefore, this sec t ion has twomajor divisions, one devoted to l and inven to r ies , l and

use produc ts , and r e la ted ac t iv i t ies , and the other to thema pp ing po ten t ia l o f Sky lab -ac qu i r ed da ta .

aPu r d u e University.bN A S A Lyndon B . Johnson Space Center .cLockheed Electronics C o m p a n y , I n c.

Principal Investiga tor .

L A N D U S E

Th e term "land use" is normal ly cons idered to in-c lude bo th th e t y p e of land cover and the ac tua l use ofth e l and as opposed to the po ten t ia l use of the l and orl and su i tab i l i ty . The actual use of the land can only bein fer r ed f rom remote ly sensed data col lec ted at any

a l t i tude ; d i r ec t in terp re ta t ion is not possible.M o s t of the invest igators w h o ana lyzed th e S k y l a b

E R E P d a t a fo r l and use determina t ion adop ted ah ierar ch ica l c lass i f ica t ion scheme based on tha t p ro -posed in the U.S. Geological Survey (USGS) Circular671 (ref. 2-1). This scheme def ined tw o m ajor l evels ofland use classification (table 2-1). Level I con ta ins n inecategories that are closely related to d i f f eren t Ear th su r -

face features (e.g . , wa ter , urban b uild up , etc .) or vegeta-tive cover types (e.g . , tundra, rangeland, forest land,

etc . ) . In Level II , these nine categor ies are fur ther sub-d iv ided , but these categor ies general ly do no t indicateth e specif ic use of the land (e.g., decid uous forest does

no t ind ica te whether th e l and is being used fo r t i m b e rproduction, for recreation, or for some o t h e r p u r p o s e ) .Such specif ic i ty is in t roduced at Level II I (e.g., recrea-t ional fac i l i t ies) and Level IV (e.g., golf courses). To fitth e var ied cond i t ions and the spec i f ic requ i r em ents in -volved in different geographical locations, most of the

inves t iga to r s modif ied th e USGS system to meet the i row n par t icu la r s i tua t ions and needs. Many f ac to r s wereconsidered by the invest igators in the i r ana lys i s and in -t e rp re ta t ion of the E R E P d a t a fo r land use purposes.

These fac tors are grouped into three m ajor categor ies:th e character is t ics of the test site, th e types o f data, and



th e i n t e r p r e t a t ive and ana ly t ic techniques used . Some ofthese factors are discussed in the fo l l owing paragraphs .

Th e spectra l contrast and geometry of sur facefeatures wi th in a g iven scene a re ex t remely s ignif icantto the o vera l l in te rpre tab i l i ty of a pa r t icu la r scene. H a n-

nah et al. (ref. 2-2) and Stoeckeler et al. (ref. 2-3)po in ted out tha t roads contra s ted w i th the sur ro und ing

green vegeta tion distinctly and c ou ld b e easily definedon the Earth Terra in Camera (S190B) color photo-g r a phs . Co lw e l l et al. ( ref . 2-4) found that , in one t y p e ofdesert scene, ten ta t ive road loca t ions tha t h ad been ex -cavated by using a bulldozer had very high ref lectancea n d , because of the lack of contrast of the roads in re la-t ion to the na tura l ly occur r ing , h ighly re f lec t ive sur -rounding soi l s , were not easily detected. Thus, th eabi l i ty to detect and i den t i fy roads or other features isoften a function of the ref lectance of the feature of in-terest in rela tion to the sur rou ndin g cover type s . Spa t ia l

cons ide ra t ions a l so a re impor tant . Long l inea r fea turessuch as roads or power l ine r ights -of -way are mo re easilydisce rned than a sma l l p in po int fea ture such a s an o i lwell , a small surface mine, or even a small water body.Th e contrast between th e par t icu la r fea ture of in te res tand the sur rounding cover types i s of ex t reme impor -tance in loca t ing , ident i fy ing , and m a p p i n g suchfeatures.

An other s i te cha rac te r is t ic tha t must be consideredi n v o l v e s t e m p o r a l v a r i a t i o n o f d a t a a c q u i r e d indi f fe rent seasons. For m u c h of the U ni t e d States, th eSky lab 2 data were obta ined during la te spr ing, theSky lab 3 da ta du r ing late summ er and ea r ly fall, and the

Skylab 4 data during winter . In many instances, th et ime of year a t w h i c h th e EREP da ta were col lec tedbecame a cri t ica l fac tor in de te rm ining the e f fec t ive useof such data . Two different investigations, Hoffer ( ref .2-5) and Poul ton and W elch ( ref . 2-6) , found that th eSky lab 2 data were less effective than the Sk ylab 3photographic da ta for vege ta t ive mapping because ofth e differences in the condi t ion of the vegeta tion duringth e sp r ing and the summer . F igure 2- 1 i l lustra tes, bycolor - inf ra red photographs , tempora l va r ia t ions in the

S an Juan Mounta ins , Colorado.Th e level of deta il in the m a p p ing s che m e to be used

is a pr ima ry fac tor in land use c la ss i fica t ion . M any in-

vestigators found that the Level I land use categoriescould be m apped wi th a h igh degree of rel iabi l i ty . Someof th e categories of Level II could be ident i f ied andmapped reasonably we l l ; others could be m a ppe d w i th

T A B L E 2-1.—A L and Use Classification System for

U se With Remote-Sensor Data

[From ref. 2-1]

Level1

Category Description

1 . 0 U r b a n a n d b u i l t - u p

land

2. 0 A g r i c u l t u r a l l a n d

3 .0 R a n g e l a n d

4.0 Forest l an d

5 .0 W a t e r

6. 0 No n f o r es t ed

w e t l a n d

7 .0 Bar r en l an d

8.0 Tundra

9 .0 P er man en t s n o w

a n d icef ie lds

Category

1. 1

1.2

1.3

1.4

1.5

1.61.7

1.81.92 . 1

2.2

2.32. 4

3.1

3.2

3.33.4

4.1

4.2

4.3

5.1

5.2

5. 35.4

5.56.1

6.27.1

7. 27.37.4

7.5

8.19.1

Level II

Description

R es iden t i a l

C o m m e r c i a l a n d

services

I n du s t r i a l

E x t r a c t i v e

Tr an s po r t a t io n ,

c o m m u n i c a t i o n s , a n d

ut i l i t i es

I n s t i tu t io n a l

Str ip an d c lu s t e r ed

s e t t l e m e n t

M i x e dO p e n a n d o t h e r

C r o p l a n d a n d p a s t u r e

Orchards , groves , bush

f r u it s , v in ey a r d s , an d

h or t i cu l t u r a l areas

Feed in g o pe r a t io n s

O t h e r

Grass

S a v a n n a s

( p a l m e t t o p r a i r i e s )

C h a p a r r a l

Desert s h r u b

D ec idu o u s

Ev er g r een ( c o n i f e r o u s

a n d o t h e r )

M i x e d

S t r e a m s a n d w a t e r w a y s

L a k e s

R es e r v o i r s

Bay s an d e s tu a r i e s

Other

Veg e ta t ed

Ba r e

Sal t f la ts

Beaches

San d o the r t han beache

Bare exposed rock

Other

T u n d r a

P e r man en t s n o w

an d icefields

8 S K Y L A B E R E P I N V E S T I G A T I O N S S U M M A R Y



\- 0 10

Sca le , km

FI G UR E 2-1.—S190A color - inf rared photographs showing seasonal dif ference s in vegeta tion for the San J u a n Mo untains of southwe stern Col-

orado. This type of seasonal scene var ia t ion in vegeta t ive condit ion was s ignif icant in data in terpreta t ion for many S ky lab inves t igat ions .

(a ) Photograph taken in June 1973 (SL2-09-017). The area s ho wn in b lu e tones indicates th e general abs e nce of green vegeta t ion , (b ) P ho t o -g r aph taken in August 1973 (SL3-21-331). Th e areas shown in several d if ferent re d hu es indicate heal thy vegeta t ion .

only moderate success. It was also found that differen t

def in it ions i n f l uenced th e apparent resul ts . In a fewcases, simi lar or even ident ical te rminology was beingused by different investigators to indicate differentlevels of difficul ty in the mapping process.

The data used in land use mapp ing were of pr ime im-portance , in te rms of both the an alyt ic techniques usedand the types of results that could be achieved. For landuse map ping , the pr im ary data were col lec ted by theMu l t i sp ec t r a l Photographic System (S190A), the Ear thTerrain Camera (S190B) , and the M ul t ispec t ral ScannerSystem (SI92). Th e inhe ren t l y better spat ial resolut ionof the S190A and S190B photographs as compared to

th e S192 imagery permit ted f lexibil i ty for the enlarge-

m e n t of the Sky l ab pho tograp hs . Desp i te th e rela t ively

small scales of the original p h o t o g ra p h s ( a p p r o x i m a t e l y1:2900000 for the S190A and 1:950000 for theS190B), more usable scales were readily obtained byenlarging th e orig inal pho tographs by us ing pho to -gra ph ic processes or view ing devices. I t was demo n-strated th at enlarged scales rang ing from 1:250000 to1:50000 were feasible and pract ica l fo r most appl ica-

t ions. Fidel i ty of i n t e rp re t a t i ve de t a il w as exce l l en t fo rthis scale range. For the higher resolution f i lms of theS190B cam era, a scale of 1:50 000 is prob ab ly the largestfo r maximum use fu l ness ; howeve r , p ro jec t ions ofS190B transparencies to scales of 1:24000 and larger

were used in detai led land us e ana l ys i s .

L A N D U S E A N D C A R T O G R A P H Y 9



General Land Use Results Obtained by

Using S190/S192 P h o t o g r a p h i c Data

Th e types of EREP land use investigations rangedfrom academic research and theoretical exam ination ofspecific photographic products and analytic techniques

to direct involvement with county planning agencies.Th e research-oriented investigators sought to determinewhy certain features on the Earth's surface appear asthey do on certain types of film and how additional in-formation can be der ived through innovative in -terpretat ive methods. The direc t-appl icat ion investiga-tions used th e photographs to extrac t information thatcould be applied in the solution of specific problems.

In the evaluation of S190A an d S190B film types forland use analysis , most investigators preferred th eS190B color photographs because of the greater spatialresolution, but other investigators indicated the needfo r the better spectral discrimination provided by thecolor-infrared film for most land use categories (m ainly

cover-type features). For discrimination of urbancategories, color film was most useful; but, fo r nonur-ban categories, the color-infrared data were better (fig.2-2). These conclus ions were substantiated by investig a-tors who used th e S190B color films as the pr ime datasource and the S190A color-infrared data as comple-m e n t a r y sources o f i n f o r m a t i o n to i m p r o v e th eclassification of natural features such as forest land,agricultural crops, r ivers and lakes, and wetlands.Figures 2-3(a) and 2-3(b) illustrate how these tw o filmtypes were used in land use planning and resource in-ventories.

Only on e investigation (Hardy et al., ref. 2-7) in -

volved the analysis of S190B black-and-white photo-graphs for land use activities. Although this type ofphotograph contains the best spatial information, effec-tive separation of Level II land units was impossiblebecause of a lack of tonal characteristics.

The two black-and-white f i lm types (panchromatican d infrared) used in the SI90A camera system showedless information spectral ly than ei ther of the color-filmtypes. The advantage of black-and-white m ult ispectralcoverage in the green, red, an d infrared wavelengths isthat different spectral responses of some land us ecategories can enhance feature identif icat ion f rom acomparative signature analysis. Additionally, each ofthe b lack-and- white bands can be combined w ith ap-

propriate filters in the photoprocessing laboratory toproduce a color-composite scene or can be enhanced by

a variety of other additive-color techniques. Spatial ly,the red w a v e l en g t h of the two b l a c k - a n d - w h i t epanc hrom atic films was judged best, but it lacked thetonal qualities required to separate some land units foridentification.

General land use mapping with use of SI 90 data.—

Most land us e investigators produced some type of landuse map as a final product by using a variety of photo-graphic data and extraction techniques. Figure 2-4,derived by pho to in terp re ta t ion of imagery an d photo-graphs, illustrates the level of land use inform atio n thatca n be obtained from different types of p la t fo rms an dsensors. Cooper et al. (ref. 2-8) compiled these land usemap s at a com mon scale of 1:63 360, using Landsat,S k y l a b S 1 9 0A a n d S 1 9 0 B c o l o r - i n f r a r ed , a n dRB-57/RC-8 aircraft imagery as the data sources. Th einterpretations were accomplished primari ly from ananalysis of t ransparencies that verified th e discr imina-tion between tonal ch aracteristics and m app ing units. Interms of hours, the compilation of these land use maps

for th e same area coverage req uired 1.5 hours fo r Land-sat, 4 hours for S190A, 8 hours for S190B, and 10 hoursfo r aircraft data. W hen these com pilat ion t imes are ex-trapolated to full-frame interpretat ion fo r each differentformat size, it is evident that satellite plat forms offer adistinct advantage over aircraft coverage. It must beemphasized that, although th e time required to compileland use maps from Landsat and S190A photographs isconsiderably less, the q uanti ty and quality of informa-tion for the S190B- and aircraft-data-derived land usemaps are m arked ly superior (fig. 2-4). The S190B photo-graph s, in particula r, were fou nd to be almost ideal fordetailed as well as regional land use maps.

A broad assortment of land use products that vary inscale, type of data used, and extent of area involved isfound in the reports of the ind ividu al investigators. Oneof these products is the detailed map of AlachuaCounty in north-central Florida (Hannah et al., ref.2-2), compiled from S190B color-infrared photographsat a scale of 1:40 000. This map was reviewed for com-pleteness an d accuracy by staff members of the Nor th

FIGURE 2-2 .—Compari son of S190B color and color - inf rared f i l m

e n la rge m e nt s acq u i re d over th e N e w bur gh , N e w Y o r k , area. T h e

higher spat ial resolut ion of the color film (fig. 2- 2 ( a ) ) is read i ly ap -

pa ren t . The color- infrared film (fig. 2- 2 ( b ) ) is useful in d i sc r i m i n a t -ing vegetation (red) an d bodies of water (black) , (a ) Color film(SL3-88-274). (b) Color- infrared film (SL3-87-300). -*-

1 0 S K Y L A B E R E P I N V E S T I G A T I O N S S U M M A R Y



S c a l e , k m

L A N D U S E A N D C A R T O G R A P H Y 1 1



Scale, k m10

FIGUR E 2-3.—A com parison of spatial and spectral charac ter is t ics of S190B color f i lm and S190A color-infrared f i lm . This scene, showing therap id ly develop ing urbanized corridor between W ashington, D.C. , an d Bal t imore, M a r y l a n d , is representa t ive of the varia t ion in spatial resolu-tion an d spectral sensitivities between Skylab photographic systems for enhancing particular land use features. For example, urban detail isvisible on the S190B photograph (f ig . 2-3(a)) , whereas excel lent enhancement of water fea tures and improved discriminat ion wi th in forestedlands are p rovid ed by the S190A colo r-infr ared pho tograph ( fig. 2-3(b)). Photograp hs were taken in A ugust 1973. (a) S190B color pho tograp h(SL3-83-166). (b ) S190A color-infrared photograph (SL3-15-172).




L e v e l I category No.

F o r e s t landW a t e r

N onforested wetlands

Barren land

0 1S c a l e , k m

L e v e l n subcategory

E x p l a n a t i o n

Color Level I category No. Level n subcategory Color

R e d Urban/built-up land 1 R esidential, single family G reen

2 R esidential, multiple fami ly Blue

3 C o m m e r c i a l

4 Industrial5 Extractive

6 Mixed7 Transportation, communi-

cation, utilities Purple8 Institutional9 Open and other W hite

Brown Agricultural 1 Pasture2 R o w crop

3 O rchard

F I G U RE 2 -4.—A com p a r i son o f L a nd sa t - , Skylab- (S190A an d S190B), a nd a i r c r a f t - d e r i ve d l a nd use maps. This f igure represents Leve l I

a nd L e ve l I I c at e gori e s m a p p e d i n t h e v i c i n i t y o f N e w bur y p or t , Massachusetts. The land use maps i l lus t ra te the type of mapp able u ni ts

t h a t c a n be d e r i ve d from i m a ge r y ob t a i ne d by us i ng t h r e e di f feren t p l a t fo r m s a nd f o u r di f feren t sensing systems. The land use c lass i f ica -

t ion system used was modif ied from reference 2-1 . Specif ic colors represent L eve l I ca tegor ies . N umb ers represent subca tegor ies , or Leve l

II i n fo r m a t i on , w i t h i n t h e L e ve l I c a t egor i es . Ha ch ur i ng i s use d i n a f e w areas where posi t ive ident i f ica t ion could not be made for a s ingle

Lev e l I c a t e gor y . T h e close cor re la t ion be tween specif ic -ca tegory pa t te rns an d a r e a l e x t e n t on t h e Skylab S190B an d a i r c r a f t m a p s sh ou l d

be no t e d , (a ) P o l i t i c a l m a p . (b ) Landsa t color -composi te land use m a p . (c ) Sk yla b S190A color - infra red land u se m a p . (d ) S ky l a b S190B

co l o r - i n f r a re d l a nd use m a p . ( e ) A i r c r a f t co l o r - i n f r a r e d l a nd use m a p .

3

12

3

4

5

6

110

1

3

Mixed

Stream

L a k eR e s e r v o i r

Bay/estuary

Tidal channelO c e a n

V e g e t a t e dT i d a l marsh

B e a c h

Other

L A N D USE AND C A R T O G R A P H Y 13



F I G U R E 2- 4 . —C o n t in u ed .

1 4 S K Y L A B E R E P I N V ES T IG A TI O N S S U M M A R Y



F I G U R E 2-4 .—Concluded .




Cen t r a l F lo r id a Reg io n a l P lan n in g Co u n ci l , wh o in d i -ca ted th a t th e map p in g accu racy an d th e q u a l i ty o fdetai l were su itable for both reg ional and county p lan-n i n g endeavors . I t was a lso compared with a recentlyreleased USGS land use map of the same area compiledfrom ai rc raf t p h o t o g r a p h s , and o n ly a few discrepancies

were noted . Class if icat ion of the to ta l county areavar ied by only 3 percent .

Coastal land use m a p p i n g f r o m th e S190B photo-graphs w a s a c c o m p l i s h e d fo r D e l a w a r e a nd M a i n e .Klem as et a l . (ref . 2-9) , us ing S190B color ph otog rap hsand a zoom transfer scope, com piled a map w ith a scaleof 1 :125 000 that del ineated 10 land use and vege tat ioncategor ies . Color - inf rared S190A photographs of the

Tru k W ate rsh ed in Main e were used to provide addi-t iona l def in it ion of water boundar ies and vegetat ivespecies.

Stoeckeler et al. (ref . 2-3) indicated that , in M a i n e ,th e S190B color - inf rared data were valuable in delineat-in g vegetat ion cover type s and cu l tural features even

though the only coverage available for evaluation was asn o w scene ( Jan u ary 1 9 7 4; fig. 18 f ro m W o o d m a n an dFarrel l 's re por t in ref . 2-3) . Logging roads th at w ere ap-p r o x i m a t e l y 6 m wide were identif ied . Several vegeta-t ion-cover - type maps were prepared f rom the S190Afilm types collected in September 1973. Ve getation

types, especially forest stands, were best interpreted

f ro m c o l o r - i n f r a re d f i l m , w i t h b l a c k - a n d - w h i t ep a n c h r o m a t i c film showing good del ineations of mostcategor ies . The remain ing f i lm types contr ibuted l i t t lead d i t io n a l information to th is overal l evaluation ofgeneral land use or vegetat ion-cover - type mapping .

Simonett (ref. 2-10) also cited several examples that

ind icated that good-qual i ty land use maps could bed er iv ed f ro m EREP d a ta . O ne su ch examp le was t heregional land use map (Level I I ) p repared at a scale of1 :126 720 f rom S190A (blac k-an d-w hite and co lor - in -f rared) p h o t o g r a p h s for St . M a r y s C o u n t y , M a r y l a n d .

Interpreting the data, map p in g the features, and prepar-in g the final map of the 1088-km 2 area required 14hours . By compar ison , a s imilar map prepared f romhigh-a l t i tude-a ircraf t color - inf rared data at the samescale required 32 hours for completion . Addit ionaldetai led information was der ived f rom the analysis but

could not be adequately d isp layed on a map of th isscale.

Hardy et al. (ref . 2-7) used a low-cost photographice n h a n c e m e n t p r o c e s s to c o n v e r t b l a c k - a n d - w h i t eenlargements to co lor composites with use of the tech-niques discussed in section 6. C o m b i n a t i o n s of spectra l

bands , d iazo hues, and exposures were selected to max-imize the co lor contras t among the land use categor iesto be examined (f igs . 2-5(a) and 2-5(b)). It should be

noted that th is process is used to ach iev e u n iqu edes c r ip t ions of classification units by means of colorcontras t ; therefore, i n d iv id u a l colors are not chosen torepresent specific land uses. In a compar ison of threetest s i tes in New Y ork , us ing the 1968 land use natura lr eso u rce (LUNR) in v en to ry as a data base, H ard yd e te rmin ed th a t m o re l an d u se in f o rm at io n was p ro -v ided by the S190A enhanced co lor composites than byth e ind iv idual S190A film typ es . In a d d i t i o n , th e co m-

posites w ere near ly as ef fective as the i n d iv id u a l S190Bfilm typ es fo r class if icat ion . Ac curacy ranges rela ted to

the USGS Level I and Level II categories for a scale of1:62 500 are s h o w n in table 2-II .

Tab le 2-III is r ep r esen ta t iv e of specif ic Level I andLevel II accuracies achieved by compar ing S190A colorcomp osites and S190B film typ es to th e ex is tin g LU N Rbase. Accuracies were determined in terms of squarehectometers, wh ich were inventoried by using film

from Skylab camera sys tems . Ran d o m g ro u n d ch ecksof the L U N R d a t a base, w h i c h w as co mp i led in 1968

T A B L E 2-11.—Accuracy Ranges fo r Level I andLevel II Categories Calculated by Using Different

Films an d Techniques

[From ref . 2-7]

Film A ccuracy, percent

Level I Level II

S190A enhanced color compos i tes 88 to 93 71 to 78

S190B three fi lm t y p e s 87 to 95 75 to 81

16 S K Y L A B E R E P IN V E S T IG A T IO N S S U M M A R Y



- ^ M -

• " " K " ? i • ' - f f i ; V- * - ^

v'

W < " *, -^%" ffi!

-*r.r"i

- . - , - * > ? ' * * & . "Î * ' ' " • • *!».,* Tt *

v J»L J*

i s lSv

v—. • • . w*«

',: % • » * • ^ n• .

4«

s

. , . - . v -

m t m -\r 7 ^/

• - • » ? - - , ''*P'i. 1. . F *--V'-

1--

- »• %

' , *\ •

^V-7 .'

>1

\ '->

w*4pi"apflfi^ Wf• ft •. i/ T -»r •Jv<*

^3p,!#iff';*:f'c-'3• */ff•;*• .. '

iwsr/ . ., y- s

Scale, km

1 0,

FIGUR E 2-5. — S190A color compos i tes of Tom pk ins Coun ty , New Y ork , showing di f ferent c o lo r en han c emen t s t ha t assist in the in terpreta t ion

of selected ca tegories . These examples represent only two of several co lor compos i tes th at wer e generated fo r th is test site. La k e C a y u g a and thec i ty of I thaca are two pr o m in en t f ea tu re s in the scene. ( A p p r o x i m a t e scale, 1:250 000.) (a ) S190A color composite designed to en han c e n a tu r a l

features , (b ) S190A color composite designed to en han c e c u l tu r a l f ea tu r e s .




from 1:20 000-scale black-and-white aircraf t photo-graphs on overlays keyed to the 7.5' topographic m apbase, indicate d an overall accuracy of 95 percent, basedon the 1973 inventory for Tompkins and Suffolk Coun-ties. However, fo r Orange County , th e accuracy was 84percent. If these adjusted figures were applied to the

SI90A data, table 2-III values wou ld increase the Skylabinventory f rom 93 to 98 percen t fo r Level I and f rom 78to 83 percent fo r Level II , with comparable increases fo rthe S190B data.

The numbers of classification units and the defini-

tions used in the LUNR sys tem ar e unrelated to theUSGS classifications for Levels I and II . Several L U N Rland us e units had to be aggregated to provide th e com-parison presented in table 2-III . Difficulty was encoun-tered in discriminating between light residential (LevelIII) and forested categories and between cro plan d andpasture. The reason for the difficulty was at tr ibuted, atleast in part, to similar spectral responses for these

categories. A s previously mentioned, th e season of datacollection is signif icant in the inventory of naturalresources. In this case, spring or late-fall coverage wo uldhave improved th e overall classification results in theLevel II categories. Hardy et al. (ref. 2-7) ranked th eS190A an d S190B sensors in terms of interpretat ionpreferences as (1) S190B color, (2) S190A color com-posites, (3) S190B black and white for spatial patterns,and (4) S190B color infrare d. The S190B blac k-a nd-white data had the best resolution properties, but tonaldistinction for the various land use categories w as oftennot sufficient to provide a high level of confidence forinterpretabi l i ty .

Ag riculture, range, forest, an d water-resource catego-

ries ar e discussed in detail in other sections of this re -port. To complete th e representation of the majorcategories in land use, attention in the next part of thissubsection is directed to the application of sample datato the urban category (with strip mining, wetlands, andother specific categories emphasized later).

Urban land use mapping with use of SI 90 data.—Pri-mari ly because of the high spatial resolution of theS190B system, almost all the investigators concernedwith urban environm ent used this system fo r detection,identification, and mapping of urban categories. Table2-IV shows a typical Level III classification un it w ith inth e "urban and built-u p land" category. This table repre-sents a compendium of the work of several investiga-

TABLE 2-HI.—Comparison of Skylab S190A

(Mult/spectral) and S190B (Color) Errors to1968

L U N R Data for the Riverhead-Southampton,

Suffolk Cou nty Test A rea a

[Skylab scale: 1:62 500)

Category 1968 L U N R area, Error, hm -

hm 2

S190A S190B

Relat ive error

S190A S1WB

Lev e l I

1 1 1

2.04 . 1 1

5.0( . ( i

' i i

9239

1 2 8 1 8

1 7 7 3 7

1 8 5 7 5

1 142484

A g g reg a t e

-155

2834

3715

55-1054

368

e r ro r

697

2369

1527

-339

-145

743

-0.02

.222 1

D O

-.92

.76

0.07

0.08

.1809

-.02

-.13

1.54

0.05

Level II

1 11.21 4

L .J

1 6

I 7

2 . 12. 2

2. 4

4 2

4. 3

5.]SJ5.35.1

( > 1( . 2

- .2

" 4

5065

261

3811 036

2 111

384

7 494

3754949

16

1 7 7 2 1

1 1 1

16 7155

18 142

4 2 !

2 2 i i

4840

A g g reg a t e

-4693

7251

-381

-348

-1599

-384

1626

-367

-4093

-163731

-111-147

-155

[11

-837

-216

3680

error

-4285

6123

43-80

-859

-344

2894

-375

-4888

-161543

-87

9 3-155

-190

-24

-120

63380

-0.93

27.78

-1.00

-.34

-.76

-1.00

2 2

-.98

-.83

-1.00

.21

-1.00

-.88

-1.00

.01

-.91

-.98

76n

0.22

-0.85

23.46

.1 1

-.08

-.41

-.90

.39-1.00

-.99

-1.00

.09

-.78

.56-1.00

-.01

-.03

-.55

1.31

oo

0.19

aFrom reference 2-7.




T A B L E 2-1V.—Urban Features Discernible on Skylab SI 90B Photographs

Level I Level II Level 111 Quali t a t ive evaluat ion of

Level III categories

1. 0 U r b a n and 1.1 Re s i d e n t i a l

bui l t -up l and

1 . 2 C o m m e r c i a l an d

services

1. 3 Indust r ia l

1 . 4 E x t r a c t i ve

1. 5 T rans p or t a t i on ,

c o mmu n ic a t io n s .

a nd u t i l i t i e s

1.6 Ins t i t u t i ona l

1 . 7 Strip and c lus t e re d

s e t t l emen t

1. 8 M i x e d

1 .9 Open an d ot h e r

1 . 1 . 1 Single- fami ly household un i t s

1 . 1 . 2 M u l t i p l e - f a m i l y h ous e h o ld un i t s1.1.3 Mobile h o m e p a r k s1 . 1 . 4 T r a ns i e n t lodging

1 . 2 . 1 Wh ole s a le t r a d e areas

1 . 2 . 2 R e t a i l t r ad e a re as

1.2.3 Business, professional, an d personnel se rvices

1 .2 .4 Cul tura l , ente r ta inment , and r e c re a t i ona l f a c i l i t i e s

1 . 3 . 1 Major m a n u f a c t u r i n g p l a n t s

1 . 3 . 2 Dist r ibut ion centers1 . 4 . 1 Stone quarr ies

1.4.2 Sand an d grave l pi t s

1.4.3 O p e n - p i t or s t r ip mining

1.4.4 Oil. gas, sul fur , sal t , an d other wells

1.5.1 Highways and re lated f a c i l i t i e s

1.5.2 R a i l r o a d s and re la ted f a c i l i t i e s

1.5.3 Ai rp or t s and related f a c i l i t i e s

1.5.4 Ma r i ne craft facil i t ies1.5.5 Telecommunicat ions an d re lated f a c i l i t i e s

1.5.6 Electric, gas , water , sewage d i sposa l , sol id w aste.

an d re lated f a c i l i t i e s

1.6.1 E duc ation al facilities

1.6.2 M e d i ca l and hea l th f a c i l i t i e s

1.6.3 Rel igious facilities

1.6.4 M i l i t a r y areas

( N o f u r t he r b r e a k d o w n )

(N o fur ther b r e a k d o w n )

1.9.1 Im p rove d

1.9.2 U n i m p r o v e d

(a )

(b )( b )

(0

(b )

(b )( d )

(b )(b )

(0(0(0(a )

(0(a )

( b )

(a )

( b )(0

(0

(b )

(c )

(0(b )

(b )

(b )

(a )

(b )

Iden t i f ic a t ion d e t e r m i n e d w i t h ease.

Iden t i f ic a t ion possible often enough to m a k e d a t a usefu l wi thou t co l l a te ra l data .

""Recognizable by geomet ry , t extu re , co lo r, and/o r a l inem ent but not pos i t ive ly iden t i f iab le unless correlated w i t h a i rc ra f t underf l ight or g r o u n d - t r u t h d a t a.

Canno t be recogn iz ed .

tors and offers a qu a l i ta t iv e ev a lu a t io n of the S190Bphotographs as they relate to urban features. Figure 2- 6is an S190B color enlargement of Jackson , Miss iss ippi ,that is representat ive of the u rban - typ e in f o rmat io npresent in such photographs . Photographs of th is typecan be enlarged to show th e spatia l rela t ionships of in-d iv idua l f ea tu r es wi th th e ad jacen t en v i ro n men ts(1:125 000 scale) or can be effectively en larged to co m-m on data-base scales (e.g., 1:50000 or 1:24000) by

p h o to g rap h ic processes or viewing devices to enablem o r e detai led urban analysis and general in terpreta t ion .

The type of urban land use in te rp r e ta t io n ac -complished by Alexander and Lins (ref . 2-11) for thePh o en ix , Ar izo n a , and New H av en , Co n n ec t icu t , areasis show n in figures 2-7 and 2-8, respec tively. A series of20 - by 20-km land use map sections w as co mp i led byusing 18- and 30-power mic rof iche v iewers and t ransfer -

r ing th e land use polygon boundar ies to scaled overlays






on wh ich l an d p a r ce l s of 4 km 2 or l a rger were m ap p ed .T h e i r ev a lu a t io n in d ica ted th a t th e S190B color photo-g r a p h s p e r m i t t e d th e d e tec t io n of h ig h e r l ev e ls of l a n du se d e ta i l th an a ny sa te l l i t e imag ery p r ev io u s ly ev a lu -a ted by u s in g p h o t o i n t e r p r e t a t i v e t e c h n i q u e s . These

areas are a lso par t of the "Atlas of Urban and Regional

Change" be in g p ro d u ced in the USGS Geograph y Pro-g r a m .T h e f o l l owi ng p arag rap h s su mmar ize th e f in d in g s

co n cern in g th e majo r Lev e l II categories and several

su bca tego r ies (Lev e l I I I ) for the P h o e n i x , A r i z o n a , an dN ew H av en , Co n n ec t icu t , s tu d ies .

Res iden t i a l : The res iden tia l land for both s i tes wasident if ied on the S190B photographs and subdiv idedinto single- and mul t i p l e - f a mi l y categor ies . The in -d iv id u a l s ignatures on the p h o to g rap h s di ffe r s o m e w h a tbetween s i tes as a function of roof composit ion , quan-

t i ty and t y p e o f v eg e ta t io n , t ime of year , lo t size, a nd

block a r r an g emen t .Commercial : Several types of commercial areas were

ident i f ied . These types include centra l business d is -t r ic t s , s t r ip d ev e lo p men ts , an d su b u rba n sh o p p in g cen -

ters. S tr ip co mm erc ia l d ev e lo p men ts ex ten d a lo n g ma-jo r transpor ta t ion ar ter ies and are usual ly no more than

one block deep on ei ther s ide of the road . Suburbans h o p p i n g centers can be easi ly identif ied a long majorsuburban h ighways by their large, brightly reflectingroofs and large, paved parking lo ts .

Indus t r i a l : Ve ry large s tructures usual ly character izeth e industr ia l category. Industr ia l act ivi ty c o m m o n l y

ap p ea r s in groups or clusters as a m i x t u r e of cro wd edlarge b u i l d i n g s , fuel s torage tanks , a nd n u m e r o u sra i l road sidings. These facil i t ies resemble shopping cen-

ters excep t that m any large build ings are present andp a r k i n g areas are not or ien ted fo r co n v en ien t access toth e bu i ld in g s .

Transp or ta t ion : The S190B photo graph s are valua blein d e l in ea t in g v a r io u s typ es of t ranspor ta t ion faci l i t ies .Maj o r high wa ys and in terchange s are clear ly v is ible andma ny lesser roads can be observed (a l tho ugh , in o lderres ident ia l areas, streets tend to be obscured by vegeta-t ion). R ailroad yards , r igh ts - of -w ay, and s id ings hav ebeen id en t i f ied . Ai rp o r t s wi th p av ed ru n ways , ap ro n s ,and p ark ing areas and wi th t e rmin a l bu i ld in g s a r ereadi ly ev id en t . Man y ut i l i ty corr idors ( i .e . , pow er l ines

and p ip el ine s) are v is ible , especially whe re they passthrough fores ted land .

In s t i t u t i o n s : In s t i tu t io n s ap p ea r in bo th scenes a n d

consis t pr i ma r i l y of ed u ca t io n a l facil i t ies and largemedica l co mp lexes . Th ey ap p e a r as groups of long, con-

nected bu i l d in g s su r ro u n d ed by extensive vegetatedareas, p a r k i n g lo ts , an d — in some cases—athlet ic f ie lds .

O p e n space: The open-space category includes im-

proved open spaces such as golf courses , cemeter ies ,p a r k s , and vacant lots. These land uses w o u l d beclassified as Lev e l IV in th i s c la s s i fica t io n ma t r ix . Th e

fa i rway patterns of golf courses are the easiest to iden-tify w i t h i n th i s ca teg o ry .

In d u s t r i a l an d co mmerc ia l co mp lexes: Al th o u g h n o ta l is ted category under Level I I I , these " in d u s t r ia lparks" were identif ied on S190B photographs . Theyusual ly co n s ist o f a mix tu r e o f in d u s t r ia l an d co mm er -cial land use, i nc l ud i ng l i gh t assembly, reg ional d i s t r i bu -t ion facil i t ies, an d research and development s i tes .These "parks" e x h i b i t none of the features associatedwi th h eav y in d u s t ry , su ch as fuel t an ks , r a i l r o ad s id in g s ,and p iles of raw mater ia ls . They are usual ly located

a long, or a t j u n c t i o n s of, majo r h ig h ways .Additional, miscellaneous activities.—As part of the

USGS Geography Program, S kyla b S190B color photo-

graphs were compared to h igh-al t i tude-aircraf t photo-graphs co l lected in 1970 fo r selected urban scenes. Th e

ma jor o bjec t ive o f th i s s tu d y was to d e te rm in e wh e th erthe S190B color photographs could be used effectivelyto d e t e r m i n e th e typ es of post-1970 land use changesthat had occurred in the 3-year in terval . This analysisw as therefore one i n v o l v i n g "change detection."

Several d i f f e r en t u rban scenes were s tudied to deter -

mine the level of detai l that could be identif ied for verydifferen t environmental areas , extending f rom a desert

sett ing to a fores ted set t ing . Only photo in terpreta t iontechniques were used to perform th e an a lys i s . A series

of over lays contain ing d if ferent land use categor ies w as

p rep a red . W h en these over lays were super imposed o nth e 1970 aircraf t-data-base land use map s , th e areas ofchange were detected (fig. 2-9). The fi ndi ngs of this in-vestigation were very positive. Th e reso lu tion of theS190B p h o to g rap h s p e rmi t ted d e tec t io n o f man y Lev e l

II I an d some Level IV categor ies ; i t approached theq u a l i t y of the h i g h - a l t i t u d e - a i r c r a f t c o l o r - i n f ra r e dphotogra phs , especial ly for the identif ic at ion and m ap-p i n g of urban changes. In figure 2-9, large parcels ofagr icu l tural land and rangeland that are undergoingchanges were me asured . From 1970 to 1973, ma ny new




A -111, Singe-family residentia

B -112, M u l t ip le - fami ly residential

C -120, Commerc ial and services

D -1 30 , Industrial

F -142, R ai l road faci l i t ies

Explanation

G - 1 4 3 , Airport facilities

K -160 , Institutions

L -170, Improv ed open space

M - 210, Cropland, pastures, an d orchards

N - 2 3 0 , Confined feeding operations

0 - 3 2 0 , Shrub-brush land range

S - 530 , R eservo i rs

Y - 760, Transi t ional land

FIGU RE 2-7.—A p or t ion of a land use map ( f ig . 2-7(b) ) der ived f rom an S190B color photograph ( f ig . 2-7(a) ) for Phoenix , Ar iz ona. This map isan e x a m p l e of a Lev e l II and Lev e l II I land use map c o mpi l ed at a scale of 1:100 000 for the P ho en ix test site. Th e m a r k e d l y di f ferent g eo g r aph i -

ca l settings (desert as opposed to vegetated landscapes) and the land us e pat terns should be noted an d c o mpar ed w i t h f igure 2-8. (a ) S190B photo-

g r aph (SL3-86-011). (b ) Land use m a p .

2 2 S K Y L A B E R E P I N V E ST IG A T IO N S S U M M A R Y



A -111, Sing le - fami l y res iden t i a l

B -112, M ul t ip le-fami ly res ident ia l

C -120, Commerc ia l an d serv ices

D -130, Indus t r ia l

E -141, H i g h w a y s

F -142, R a i l road fac i l it i e s

G -143, Airport fac i l i t ies

H -144, Uti l i ty r i ghts-of-way

Exp lana t i on

I -145, M a r in e craf t fac i l i t ies

J -150, Indus t r ia l and commerc ia l complexes

K -160, Ins t i t u t ions

L -170, I mproved open space

M-210, Cropland, pastures, and orchards

P -400, Forest l and

Q -510, Streams an d canals

R -520, L a k e s

S - 530, R ese rvo i rs

T - 540, Bays and estuaries

U - 610, Forested wet land

V - 620, N on fo res ted w e t l and

W - 720, Beaches and mudf la ts

X - 750, Str ip mines, quarr ies,

and grave l p i ts

Y - 760, T rans i t i ona l l and

F I G U R E 2-8.—A portion of a l and use map (f ig. 2-8(b» der ived from an S190B color photograph (f ig. 2-8(a )) for New Ha ve n , Conne c t i cu t . Thi sexample of Level II and Level II I l and us e categories represents the type of informat ion t ha t can be useful fo r regional plannin g and land use in-

ventor ies . T h i s map was compi led by us i ng a 1:100000-scale S190B p h o t ogr a p h t a ke n S e p t e m be r 19 , 1973.Th e ove r a l l scene contras t an d l and

us e pat terns of th is f igure should be compared wi th those of f igure 2-7. (a ) S190B photograph (SL3-88-276). (b ) L a nd us e map.




E xp lanation

A-Y

Scale, k m

F I G U R E 2-9 .—A port ion of a Leve l II and Level II I l and us e ch angemap for the Phoenix test site. A dot p lanimeter was used for area

measurement to permi t calculat ion ( in percent ) of total amount of

change in the test site fo r each category. (Fig. 2-7(a) contains aphotographic d i sp lay of th i s area. )

L A N D US E CHANGE -

F irst letter indica tes 1970 landus e

interpretation:second le t ter indicates 1970-73 chang e in land use.

A -111, Sing le-family residential

B -112, M ult ip le- family resident ia l

C -120, Commercia l an d serv ices

K -160, Institutions

L -170, Improved open space

M -2 10 , Cropland, pastures, and orchards

0 - 320 , Shrub-brushland range

S - 5 3 0 , R ese rvo i rs

Y -760, Transit ional land

Z N o change in land use

res ident ia l areas were developed and w ere ma pped onth e S190B pho togra ph s . A rea s tha t s how ed ev idence of

some activity bu t tha t could not be accurately classifiedwere placed into the t rans i t iona l ca tegory (symbol Y infig. 2-9). M a pp ing o f nonurba n l a nd us e ca tegorie s,how eve r , w a s more di ff i cu l t wi th the use of S190B color

p h o t o g r a p h s . F o r e x a m p l e , f o r e s t s tended t o beu n i fo rm l y green on the na tura l -color f i lm, a nd w ooded

resident ia l areas w ere di ff i cu l t to d i s c r imina te in s ome

cases. Repe t i t ive t empora l cove ra ge w i th use of a h i g h -resolut ion color- infrared f i lm in the S190B camerawou ld imp rove the inte rpre tabi l i ty of these ca tegories .

In a c l a s s i f i ca t ion a ccura cy s tudy , A lex a nde r a nd

Lins ( ref . 2 -11) used th e S190B color- f i lm d a ta to pro-duce a 1:24 000-scale lan d use map of Fa i r fa x C i ty ,

Virginia . This m ap p r o d u c t w as evalua ted aga ins t as imi l a r ma p p repa red f rom high-al t i tude-ai rc raf t (U-2)color - infrared pho togra phy a t t he s a me s ca l e a nd w a s

field checked fo r a ccura cy . A n accuracy of 83 pe rcen tw a s ach ieved w i th the E R E P da ta fo r m a pp ing Leve l II Il a nd un i t s w hen compa red to the aircraft data base. Toquant i fy th e re s u l t s , A lex a nde r used tw o methods todetermine the accuracy of the resultant maps. First, a

sys tematica l ly a l ined sample (grid ce l ls ) of 69 sample

points w as e x a m i n e d ; an d second, th e area measure-ments (square hectometers ) of the land uni ts were com-pi led fo r both th e Sky la b and the a ircraf t da ta maps . O fthe 69 sample points , 57 were c orrect ly c lass ified. Of theunits tha t were misclass if ied, nearly ha lf th e error w as

2 4 S K Y L A B E R E P I N V E S T I G A TI O N S S U M M A R Y



a t t r i bu t ab l e to the lack of sp ec t r a l d i s c r im in a t io n in thecolor film. Full fo l iage cover made detection of housesor o ther res identia l "keys" impossible . This di ff i cu l ty isalso true fo r high-a l t i tude-a i rcraf t data.

An o th er source of error was the d i f f i c u l t y of iden-t i f y i n g a n d m a p p i n g t h e u n i m p r o v e d o p e n - s p a c e

ca tegory . These areas were confused wi th small p lo ts ofagr icul tura l land . In a summ ary of the S190B data , Alex -ander and Lins (ref . 2-11) indicated an abi li ty "to dis-t inguish and map with considerable conf idence suchs t ruc tu ra l urban details as the location and extent ofmost sing le-family residential areas, even some res iden-tial s tructures themselves , commercial and in d u s t r ia lareas , even i ndi v id ual comm ercial and in dustr ia l s truc-tures, streets and roads of moderate size and consider -able detail in the use p a t te rn s of su r ro u n d in g n o n u rbanland. If color infrared film of com parable spatia l reso lu-tion to that of color film used in th is evaluation hadbeen availa ble the investigators are conf ide nt that evengreater detail and r e l i ab i l i ty of detection of the various

land use categories would have been obtained . . . . TheSkylab S-190B d ata here revealed a capab ility to dis-t inguish Level III and in some cases, Level IV (tra i lerparks , tank farms, go lf courses , drive-in theaters, ceme-teries, etc.) in urban area land use analysis." Results ofother investigators (Hannah et al , ref. 2-2; Simonett,ref. 2-10; and Bald ridge et al., ref . 2-12) generally sup -ported these f in d in g s .

W h e n a su itable inventory data base (such as anaircraft mosaic) is available for an area, it is quick an deasy to update that data base by using S190B-typephotographs . Although th e S190B color photographsprovided th e m os t mea ningful source of information toupdate inventory bases in most land use inventor ies ,

th e multispectra l character is t ics of the S190A alsoproved valuable. In several cases, th e information pro-v ided by S190A film typ es w as extremely benef icia l tothe analysis as a supplementary source for identif ica-tion and delineation of specific non urba n c ategories.Fo r examp le , in forested or generally vegetated scenesfor which S190B color film was the primary source ofdetai led informa tion , the S190A color - inf rared f i lm pro-v ided addit ional spectra l information .

The pattern and extent of urban expansion in topr ime agr icu l tu ral land were mapped for C olumbus,Ohio , by Ba ld r id g e et al. (ref . 2-12), with the use ofS190A ph otograp hs (fig. 2-10). W ith use of the map

data, percentage figures were calculated to determinethe rate of encroac hme nt. This type of analysis, whe n

coup led with long-range populat ion density and p a t te rnproject ions , can be meaningful to urban and reg ionalplanners and to decisionmakers; it can also be used asan input to tes t and update pro jection- type models .

In o th er u rban - r e la ted ac t iv i t ie s , W elby an d Lam mi(ref . 2-13) used Skylab p h o t o g r a p h s fo r s t u d y i n g en -

v i r o n m e n t a l issues involved with the expansion of theR a l e i g h - D u r h a m , North Caro l ina , a irpor t . Pressure toexpand airpor t facil i t ies (run wa y extensions , or ien ta-t ion of new ru nw ay s, e tc .) created p roblems c oncern ingeffective p l a n n i n g fo r th i s exp an s io n wi th th e least

a m o u n t of adverse effect on the local area. Althoughthe decis ionmaking process for th is type of problem iscomplicated and is inf luenced by social , po l i t ical , an deconomic factors , W elby and La mm i concluded th atSkylab photo graphs , even when used by a rela tive ly in-exper ienced p hoto in te rpreter , are usefu l for th is type ofe n v i r o n m e n t a l an a lys i s .

Another urban environmental problem in whichSkylab photographs w ere used by W elby and Lamm i in -

volved a "greenspace" s tudy. In urban p l anning , agreenspace (or greenbelt) is defined as an area of landcovered with some form of vegetation. Planners areconcerned wi th this typ e of area in terms of how to pro-

tect and manage i t ef fectively and how to obtain addi-t ional areas when needed. The S190B color photo-graphs, enlarged to a scale of approximately 1:62 500,prov ided the best source of, and format for, relevant in-formation for greenspace analysis.

W e l b y and Lammi summarized their use of S190Bcolor photographs with the fo l lowing s ta tements .

Land use, vegetative cover, an d even th e rela t ivebea u ty and ugliness of the urban landscape can b e

seen or infer red f rom the photographs . The prox-imi ty and encroachment of commerc ia l - indus t r i a l

developm ent in to good qua l i ty res identia l areas ,the tendency of many new res identia l develop-m e n t s t o b e c o m e o p e n b u l l d o z e d b i o l o g i c a ldeserts a re examp les o f th e en v i ro n m en ta l qual i ty

problems v is ible in S kylab Ph o to g rap h y .

Another use of ER EP data w as explored by d ig it iz -in g S190A and S190B photographs for generating landuse classification map s. Hann ah et al. (ref . 2-2) orientedtheir approach toward a direct appl icat ion fo r urbanplanners, whereas Silva (ref. 2-14) directed h is efforttoward a quanti ta t ive , technical evaluation by compar-

in g the d ig it ized photographic resu l ts wi t h Landsat andSkylab multisp ectra l scanner resul ts.




Urbanized areas, 1962

Urban g rowth , 1962-73

Townships containing most

product ive agricultural land

10

Scale, km

FIGURE 2-10.—Map of Franklin C ounty, Ohio, showing urban encroachment on agricultural land in the Columbus, Ohio, area . This m apgraphical ly por trays th e area! extent and pat te rn of urba n encroachm ent into three predominant ly agricultural townships surrounding Colum-bus . Convent ional photographic techniques with the use of S190A photographs were used to plot the limit of the 1973 built -up area .




For the Gaine svil le , Flor ida , site, Hannah et a l .generated a Level II class if icat ion m ap f rom threeban d s of d ig i t iz ed S 1 9 0B co lo r - in fr a r ed mu l t iem u ls io ndata . The resu l t ind icated that ident i f icat ion of var iousland classes on the basis of color tones can be ac-co mp l i sh ed mo re effectively by the h u man o bserv er

(pho to in te rp re ta t ion ) ; examp les in c lu d ei den t i f y i ng

forest types and o ther vegetat ion types , such asw a t e r h y a c i n t h s and m arsh land s , and rela t ing land useunits to their sur roundings . By contras t , the maps pro-duced wi th co mp u te r assistance reveal more details in-vo lv ing co mmerc ia l - in d u s t r ia l classes because of thecapabi l i ty of mach ine processing to impr ove the degreeof brightness of the spectral responses .

S i l v a d i g i t i z e d b o t h S 1 9 0 A c o l o r - i n f r a r e d(mul t i emul s ion) and S190A mu ltib and data , us ing thefour - ba nd black-an d -wh i te in f r a r ed f i lms obtained overthe Lake M onroe, Ind iana , s i te . A class if icat ion perfor -

mance analy sis based on t r a in in g fields fo r nine landus e classes w as performed. Table 2- V sh o ws th e resultscompared to the Skylab S I9 2 an d L an d sat mu l t i sp ec t r a lscanner data for the s a m e a rea . Al th o u g h th e p er f o r -mance levels were lower than those of the best fourbands of the S kyl ab m u l t i sp ec t r a l scanner (bands 3, 7 , 8 ,

and 11 ) and those of the Land sat mu lt ispec tra l scannerbands , th e mult iemuls ion data were better than th edigitized m u l t i b a n d b l a c k - a n d - w h i t e d a ta .

B o t h i n v e s t i g a t o r s i n d i c a t e d t h a t , a l t h o u g h t h eachieved resu l ts were undramatic , d ig it ized photogra-phy is a t ech n iqu e fo r which research and d e v e l o p m e n tshould be co n t in u ed fo r land use resource and in v en to -ry programs.

In th e fo l lowing subsections, land use results ob-ta ined by using S192 imagery and co mp u te r - a id edanalysis techniques are discussed.

T A BL E 2- V.—Classification Performance R esults: Digitized SI 90A

Photography Compared to Data From Two Multispectral

Scanners for Selected Categories

[Percent cor rect ]

Category

R es i den t i a l

C o m m erc i a l - i n du s t r i a lE x t r a c t i v e

Soil

GrassSparse woods an d deciduous forest

C o n i f e ro u s forestR i ve r

L a k e

Class average"

O v e r a l l p e r fo r m a nce ^

Skylab

B an ds

3, 7. 8, 11

97

73;:

8 795

8 1

9987

89

84

87

S192

Bands

3. .\ 6, 8

8 1

5 359

7 8

g6S I ]

6827

86

66X I I

Landsat

scanner

• > -

6 16 1

8 393

g6

95

77

86

82

8J

Skylab

Color

infrared

91

7 6> 2

678 2X 4

85

1 6

98

70

83

S190A

Four-band

black an d

white

84

(634

7869

7743

6493

65

76

aAr i i hmeuc mean of t he per for mance r es ul t s of t he nine c l as s es .

' 'Total num ber of point s c l as s i f i ed cor r ec t l y d ivided by t o l a l nu mber of point s i n test areas, t imes 100.




General land use mapping with use of SI 92 data.—Several investigators (Hannah et al., ref. 2-2; Hoffer,ref. 2-5; Klemas et al., ref. 2-9; Simon ett, ref. 2-10; Silva ,ref. 2-14; Gilmer and W ork , ref. 2-15; Higer et al., ref.2-16; Polcyn et al., ref. 2-17; and Sattinger et al., ref.2-18) used computer-aided analysis techniques for the

study of Skylab S192 data obtained over m any test sitesto map a variety of different types of land cover. Theresults, in general, indicated a considerable po tential form a p p i n g various land cover types through use of thesetechniques, even though th e procedures used to trainth e compute r , th e classification algorithms, and themethod s used in eval uatin g the results varied considera-bly. Some of the investigators conducted detailedanalyses to determine the wavelength bands that weremost valuable for mapping different cover types. Theseresults show the value of the spectral range of the SI92system. Because some studies also involved analysis ofLandsat-1 data obtained over th e same test site as theEREP data , valuable comparisons of results obtained

by using two very different satellite multispectral scan-ner systems were possible.

Most of the investigators used th e USGS Circular67 1(ref. 2-1) system of land us e classes in their analyses butmodified it to meet their own particular requirements.In many studies, both Level I and Level II degrees ofdetail were mapped; and in some investigations, moredetailed classifications were achieved for selected covertypes. For the Level I cover types, th e classification ac -curacies ranged from approximately 72 to 91 percent.For the Level II degree of detail , th e results were morevaried, with overall classification accuracies rangingfrom 43 to 89 percent. The exact reasons fo r these varia-tions in resul ts cannot be specif ical ly determined. It is

difficult to isolate the reasons for the variation s becauseth e different investigations involved diverse test sitesthat included a wide variation of cover types. Distinctdifferences in the ana lysis and evaluation techniquesalso must be considered.

Th e following paragraphs provide some insight intoth e s imilari t ies an d differences among th e many in -vestigations by summarizing key aspects of the variousstudies. Only those investigations involving land us eand land cover mapping by computer-aided analysistechniques are included here. Unless otherwise noted,each of these studies involved SI92 data that had beendigitally fil tered and line-straightened at the NASALyndon B . Johnson Space Center data-processingfacility.

A s tudy by Simone tt (ref. 2-10) involved th e analysisof S192 data over a pred omin ant ly urbanized test s ite inth e Washington-Bal t imore region. The data were ob-tained on August 10,1973, and all 13 wavelength bandswere avai lable fo r analysis. Extensive fieldwork pro-vided th e informat ion fo r identifying many areas that

could be located in the S I92 imagery . A clustering tech-nique was used to help define spectrally homogeneoust ra in ing an d test areas. The classification w as per-formed by using a max imum -l ikel ihoo d a lgori thm s imi-la r to that used by several other investigators (Polcyn,Silva, Hoffer, and Sattinger; refs. 2-17, 2-14, 2-5, and2-18, respectively). A major difference in Simonett 's ap -proach was that a two-stage classification sequence in-volving different combinat ions of wavelength bandswas used. This approach differed from that used by theother investigators because they generally defined asingle optimal set of wavelength bands fo r classifyingthe da ta at the Level II degree of detail. The results ofthis Level II classification were then gro uped into

broader categories to display and tabulate Level Iresults.

Simonett defined five major Level I classes in theW ashington- Baltimore test site: urban, agricultural,forest, water, an d wetlands. Th e results were quan-titatively evaluated by using a series of test areas that in -cluded approximately 13 600 pic ture elements (pixels),of which more than half (7000) were in the urbancategory. Simonett reported a 72-percent classificationaccuracy for the Level I classification of the test areas.This result compared w ith 73 percent for the trainingdata sets an d indicates that a f a i r l y good statistical sam-ple existed for both the tra ini ng data sets and th e testareas. Results obtained by using a combination of the

t ra in ing an d test pixels (approx imately half of each) areshown in table 2-VI. Th e Level II classification resultsyielded a classification accuracy of approx ima te ly 43percent. Significant misclassification occurred at theLevel II degree of detail in the agricul ture an d forestcover types, although other investigators reportedreasonably good classification performances in similarcategories of cover type. In some study sites, the num-ber of training and test areas was insufficient to trulyrepresent the various categories invo lved at thi s level ofdetail. As a result of this relatively poor classificationperformance at the Level II degree of detail , Simonettconcluded that, in this particular study, only th e Level Iclassification results would be of potential value forland use planning agencies. This general land use in-




vestigation also included a de ta i l ed eva l ua t ion of

spect ral bands for land use studies. The resul ts of s imi-la r eva l ua t ions a re discussed in the subsect ion ent i t led"Urban land u se m a p p i n g w i th use of SI92 the rma l - in -fra red data . " Simonet t ' s conclusions, together wi ththose of other invest iga tors , are discussed in the subsec-

t ion ent i t led "W avelength b and evaluat ion ."T h e Brevard Coun ty P l ann ing D e p a r t m e n t i n

Flo r id a conduc ted a l and use inves t iga t ion t ha t i nc l udedcomputer-aided analysis of the S192 data (ref. 2-2). Asupe rv i sed approach w as used to develop th e t ra in ingstat i s t ics for the analysis; and, as in other invest iga-t ions , a m aximu m-l ike l i hood - ra t i o a l gor i t hm was usedfo r the c lassi f icat ion. To obtain ou tpu t products for landuse planners, th e general ized boundaries of c o m p u t e r -generated land use classes were manual ly de l ineated.The invest igators indicated that acceptable resul ts wereobtained and th at mul t i spect ral scanner m ap pin g was auseful tool . In general , th e computer c lassi f icat ion mapstended to have m o r e precise qu ant i ta t ive ly def ined landu se pat terns, whereas resul ts f rom photointerpre tat iontended to generalize some of the pat terns. Thisdif ference resulted in an overestimation of forest areason the photointerpre ted resul ts as compared to the com-puter-der ived resul ts .

In a study by Polcy n et al . (ref. 2-17 ), the SI9 2 datawere used to c lassi fy an area in southern Ontar io ,Canada, large ly covered by vegetat ion. The cover types

involved in the c lassi f icat ion included marsh, coni -

f e r / h a r d w o o d , h a r d w o o d / o r c h a r d , u n d i f f e r e n t i a t e dvegetat ion ( i nc l ud ing b rus h , i d l e , e t c .) , suburban , bareso i l / qu a r ry , herbaceous vegetat ion, and w ater . On lyfour wave l eng th bands of the S192 data from th e S k y l a b2 mission (0.56 to 0.61, 0.62 to 0.67, 0.78 to 0.88, an d10.2 to 12.5 /u.m) were ava ilab le fo r ana l ys i s . The t r a in -

in g stat i s t ics were obtained by a p p l y i n g tw o successiveclustering-step analyses. The classification w as based ona m a x i m u m - l i k e l ih o o d a l g o ri t h m , as incorporated intoth e software system. Because of the di f f icul ty in

developing an adequate se t of test areas fo r eva l ua t ingth e classi f icat ion resul ts , Polcyn developed a d i f fe ren tapproach fo r q ua n t i fy ing th e resul ts . This approach in -

volved def ining th e " p r o b a b i l i t y o f correct classifica-tion" for the eight categories mapped, based on as ta t is t ical ana lysis of the t rain ing data. The resul ts indi -cated tha t al l categories except tw o h ad p roba bi l i t ies ofcorrect c lassi f icat ion above 90 percent . (Undifferent i -ated vegetation and suburban categories h ad prob -abilities of correct c lassi f icat ion of approximate l y 78

percent . ) The training stat i s t ics that were used as a basisfo r these qua nt i tat iv e evalua t ion f igures represented thebest classification statistics. Polcyn also noted that thean a lys i s i nd i ca t ed a l ikely misclassi f icat ion of thesu bu rban category as e i t he r "brush" or "bare soil"; th isconclusion is not surp r ising because a suburba n area isoften composed of a m i x t u r e of cover types that wouldinclude these spectral classes.

T A B L E 2-Vl.—Skylab Classification Results for the Heavily U rbanizedBaltimore- W ashington A re a

[From ref . 2-10]

Ground- t ru th N o.

category of

pixels

Skylab classification results, percent

WOO:

Urban

2000:

Agricul tura l

4000:

Forest

5000:Water

6000:

Wetlands

Percent

classified

correctly

1000: Urban

2000: A g r i c u l t u r a l

4000: Fo r es t

5000: W a t e r

6000: W e t l a n d s

T ot a l

12 99 3

7 4 5 1

1 71 3

1 549

928

2 4 6 3 4

71.3

17.3

4.0

1 0

4 4

19.3

69.45.1

.3') ;

/ 4

11.3

84.1

.3

33.6

0.5

. 11 .1

96.3

6.6

1. 5

1.9

5. 7

2. 1

46.1

7 1 . 3

69.4

84.1

96.3

46.1

a

72.2

Percentage reflects correct classificat ion of 17 796 p ixel s .




Silva (ref . 2 -14) , us ing unfi l te red SI92 da ta obta ined

on J u n e 1 0, 1973, over th e L a k e Monroe area in s ou th -cen t ra l Ind ia na , conduc ted a l a nd us e s tudy tha t i den -

t if ied re s iden t i a l , comm erc ia l - ind us t r i a l , ex t ra c tive , s o il ,

grass, deciduous fores t , coniferous fores t , r iver , and

lake . (Note t ha t , in some instances, the inves t iga to rs

w ere w ork ing w i th l a nd cove r cha ra c te r i s t i c s ra the rt h a n l a n d uses, such as "soil," w h i c h w o u l d a c t u a l ly b e

in t he a g r i cu l tu ra l c rop la nd l a nd us e ca tegory . ) A com-

b i n a t i o n of s upe rv i s ed a nd c lus te r ing a na ly s i s t e ch -

n iq ues w a s used to develop the s ta t is t ics for c lass if ica -

t ion. A d ive rgence processor was used to define the best

c o m b i n a t i o n of 4 of the 12 w a ve leng th ba nds a va i l a b le

fo r use. This process ind ica ted tha t ba nds 3 , 7 ,8 , a nd 11

represented the best c o m b i n a t i o n . It a ppea red tha t

these w a ve leng th ba nds a l so gene ra l ly h ad th e best data

qu a l i t y a m o n g those a va i l a b le . The re fo re , t he re w a s

some conce rn as to w h e t h e r those ba nds w e re be ing

selected for the ir spectra l character is t ics or for the ir

da ta q ua l i ty or for a c o m b i n a t i o n of b o t h . Th e classifica-tion w a s c o n d u c t e d b y u s i n g a m a x i m u m - l i k e l i h o o d

ra t io based o n t h e m u l t i v a r i a n t Gaussian d i s t r i b u t i o n a s

incorpora ted in to the s o f tw a re . A n o ve ra l l c l a s s i fi ca t ion

a ccura cy of 87 p e r c e n t w as ob ta ined , based on ta bu la -

t ion of the results in the test areas. In t h i s pa r t i cu l a r set

of resul ts , the test areas selected did not rep re s en t a

s ta t is t ica l ly defined array of test areas, and Si lva ( ref .

2-14) s ta ted tha t these pe r fo rma nce f igu re s migh t ha ve

been somewhat biased in an upw a rd direction. It is im-

p o r t a n t to note tha t this resul t is based o n a Leve l IIdegree of deta i l ; therefore , i t does ind ica te a po ten t i a l l y

signif ican t i m p r o v e m e n t over th e class if ica t ion ac -cura cy reported b y some of the o the r inves t iga to rs fo r

this level o f deta i l . A m a p d i s p l a y of these class if ica t ion

results is shown in f igure 2-11.Addit iona l ana lyses of the SI92 data over south-

cen t ra l In d ia na w ere p e r fo rmed by S i lva , u s ing asta t i s t ical ly defined set of test areas. Many class if ica -

tions of the test areas w ere conduc ted ; d i f fe ren t num-

bers and c o m b i n a t i o n s of w a ve leng th ba nds w e re used,

fo r bo th the in te r im un f i l t e red a nd digi ta l ly f i l te red da ta

sets. The best class if ica t ion resul ts were obta ined withsix wavelength bands (2, 3, 7, 9, 10, and 11) of the

f i l te red da ta se t and the weighted a pr i o r i proba b i l i t i e s

(as opposed to eq ua l a p r io r i p roba b i l i t i e s ) . For the s ix -w a v e l e n g th - b a n d c o m b i n a t i o n , th e ove ra l l c l a s s i f ica t ion

p e r f o r m a n c e a ccura cy was 92 p e r c e n t fo r Leve l I and 90pe rcen t fo r Leve l I I . For the be s t four w a ve leng th ba n ds

(3 , 7 , 8 , and 11) , the L evel I accuracy was esse nt ia l ly as

good, 91 pe rcen t , a nd the L eve l I I accura cy w a s 89 pe r -cent . Table 2-VII shows the resul ts of the c lass if ic a t ion s

fo r both Level I and Level II land use classes, based on

the tes t - s i te da ta .

A s t u d y b y Satt inger et al . ( ref . 2 -18) involved proc-

ess ing of the SI92 da ta for appl ica t ion to recrea t iona l

land ana lys is . The tes t s i te was of primary va lue for

TABLE 2-VII.—Level I and Level II La nd Use

Classification Results for an A r e a in Central Indiana

[ F ro m ref . 2 -14]

L a n d use category Percent of test-area pixels classified correctly

Optimum s i x ba nd sa

Optimum four bandsb

Level I Level II Level I Level II

U r b a n

Resident ia l

C o m m e r c i a l -

i n d u s t r i a l

E x t r ac t i v e

A g r i cu l t u r e

Soil

Grass

Forest

D e c i d u o u s

Coni fe r ous

W a t e r

R i v e r

L a ke

O v e r a l l

77.2 78.580.2

71.9

50.0

88.7 88.9

93.586.0

93.7 92.7

92.256.4

98.1 96.189.2

98.991.6 89.7 91.1

79.1

75.0

65.4

95.3

86.2

90.4

59.0

73.0

98.5

88.8

"Bands 2. 3. 7. 9. 10. and 11bBands 3. 7, 8, and 11.

30 S K Y L A B E R E P I N V ES T IG A T IO N S S U M M A R Y



% - r . ; ^

Ss^» — - j» >

* . *

r Yv > . v« » c

>,

i i j f - K*

L p .¥'-k\» * .

L»f\~' " '

F-^gfc^5 r;<i-^ ^;H . :-^.*

> V

x jîf^--^: > /

J

J- „.-*•* • -*i

..r 7 » *

,\

' SP4?2-vft^ f- *>V-

lr'-» - vY' T

4

^^v^1" g -

*-V*->- v-lf:r**f

ISS? JP i' -v^

>?<

R e d R e s i d e n t i a l

Dark gray Commercial-industrial

C r e a m E x t r a c t i v e

iK«iS ,E x p l a n a t i o n

Y e l l o w B a r e s o i l Pink Coniferous f o r e s tLight green G r a s s Light blue RiverD a r k g r e e n D e c i d u o u s f o r e s t D a r k blue L a k e

^

0*

0 5

Sca le , km

F I G U R E 2-11.—Color-coded c l a s s i f i c a t i on us i ng S1 92 m u l t i sp e c t r a l s ca nne r d a t a fo r a n ar e a sou t h o f B l oom i ng t on , I nd i a na . Mo nr oe L a ke i s a t

th e top. N i ne l a nd us e classes ar e represented . Bands 3 , 1 , 8 , and 11 were used fo r th is c lass i f ica t ion. (Scale of or igina l , 1 :240000.)




wildl i fe h abi ta t an d in v o lv ed a r e la t iv e ly sma l l (5300

h m 2), mostly forested State game area in centra lM i c h i g a n . A m a x i m u m - l i k e l i h o o d a l g o r i t h m w a s used

for the class if icat ion . A to ta l of 35 spectra l t ra in ing

classes w as in i t ia l ly def ined; these classes were thenco mb in ed to f o rm 1 0 ma jo r in f o rm at io n a l catego r ies .

S ix wav e len g th ban d s were used for the class if icat ion ,based o n a c o m p u t e r e v a l u a t i o n of the o p t i m u m c o m -

bin a t io n f o r t h i s p a r t i c u l a r a n a l y s is . T h e w a v e l e n g t h

ban d s used, in order of preference, were 0.78 to 0.88,1.55 to 1.75, 0.98 to 1.08, 0.68 to 0.76, 0.52 to 0.56, and

0.62 to 0.67 p tm. Th e c la s si fied d a ta were qu an t i ta t iv e lyev a lu a ted by a su mm ar iza t io n o f th e a r ea o f th e v a r io u s

cover types over three 2.6-km 2sections of l an d , and by a

d e ta i l ed qu an t i ta t iv e co mp ar i so n of the classified data

wi th th e Mich ig an Dep ar tmen t o f Na tu r a l Reso u rcescover - type maps. These ev a lu a t io n s in d ica ted th a t th e1 0 i n fo r m a t i o n a l classes had been map p ed w i th o n ly a54-percent class if icat ion performance. Consolidation of

the 10 classes in to 5 more general ized categor iesresu l ted in an accu racy of 72 p er cen t . Th is lo w level ofaccu racy is a t t r ibu ted to the c o m p l e x i t y of the test site,

as in d ica ted by the measure of m a n y s m a l l stands, aco n d i t io n th a t r esu l ted in m a n y "edge" p ixe l s , o r p ixe l sc o n t a i n i n g more th an a single cover type. Such factors

are i m p o r t a n t to consider in class if icat ion . Satt inger(ref. 2-18) stated tha t S192 data can be used fo r reg ionalsurveys of exis t ing or potentia l recreational s i tes , ford e l in ea t io n of open-space areas, and for p r e l i m i n a r ysite

ev a lu a t io n of g eo g rap h ica l ly ex ten s iv e sites.

Th e Green S w a m p in centra l Flor ida w as investi -gated by Higer et al. (ref. 2-16); S192 data were used top rep a re maps sh o win g en v i ro n men ta l ca teg o r ies . T h e

Green S w a m p is not a co n t in u o u s exp an se of s w a m p ,bu t a co mp o s i te o f ma n y swa mp s wi th in te rsp er sed lo wridges , h i l ls , and f iat lands. The water , l an d , a nd vegeta-t ion in the area are undergoing rap id changes caused bylogging; reforesta t ion ; a l terat ion o f natural drainage bych an n e l iz a t io n an d ponding; a n d bu rn in g a n d clear ing

fo r such purposes as sod f a rmin g , c i t r u s f a rmin g ,p a s t u r e i m p r o v e m e n t , a n d u r b a n a n d i n d u s t r i a l

development. Imp ro p er p lan n in g a nd co n s t ru c t io n o fnew industr ia l and res identia l areas could clear ly have adisastrous effect on such an en v i ro n men ta l ly sen s i t iv earea. For th is reason, cu r r en t co v er - typ e map s are

urgen t ly needed for use in en v i ro n men ta l ap p ra isa l s to

develop a ra t ional basis for fur the r p la nni ng and con-

tro l led development. Higer 's s tudy was d irected a tevaluating the usefu lness of Skylab SI92 data for t ime lyin te rp re ta t ion , assessmen t, an d m ap p in g o f en v i ro n -

mental categor ies . These ca tego r ies in c lu d ed wet lan d s ,water , cypress , p ine, pasture, a nd uplands . A co mp u te r -

a i d e d a n a l y s i s t e c h n i q u e , i n c o r p o r a t i n g s u p e r v i s e d

class if ica t ion, was used . Af te r class if icat ion , a qual i ta -t iv e ev a lu a t io n of the resu l ts w as co n d u c ted th a t in -volved compar ison of the class if icat ion maps and aerialp h o to g rap h s of the s tudy area . These co mp ar i so n s ind i -

ca ted th a t th e categor ized S192 data were "found to bet ru ly r ep r esen ta t iv e l an d -wa te r co ver c o n d i t io n s in th eGreen S w a m p area." These results are discussed fu r t h e r

in the subsection enti t led "Com par ison of Sky lab S192

an d Lan d sa t m u l t i sp ec t r a l s can n er analyses."

K l e m a s et al. (ref. 2-9) used th e S192 data and a com-p u t e r i n t e r a c t i v e s y s t e m to p e r f o r m a l a n d u s eclassification of p a r t of the Delaware B ay area. Thesys tem a l lo wed a max imu m o f o n ly four wav elen g th

bands and eight spectral classes to be used in a singleclass if icat ion . Bands 4, 6, and 8 we re selected becausethey roughly correspond to three of the Lan d sa t bands;

band 11 was included because o the r investigators havesuggested that the use of wavelengths fur ther in to th eref lect ive inf rared could increase land use class if icat ionaccuracies. Th e eight classes identif ied were water , sandand bare sandy so il , sa l tma rsh c ordgrass , fores t land ,bu i l t - up l an d , p lo wed f ields , cropland (p lan ted f ields) ,

and a class composed of catta i ls and g ian t reedgrass.

The class if icat ion resu l ts were d isp layed one class at at i m e and ev a lu a ted qu a l i ta t iv e ly . Th e investigator

showed t h a t class if icat ion accuracies ranged f rom 100percent for water to 44 percent for the bu i l t -u p - l an d

ca teg o ry . In the l a t te r g ro u p , most of the errors inc l a s s i f i c a t i o n were d u e t o c o n f u s i o n w i t h t h eagricul tura l ca teg o ry . H o wev er , p h o to in te rp r e ta t io n o fEREP S190A/S190B data indicated an accuracy fo rbuilt-up areas of 81 percent . Klemas indicated that th eresults represented "a co n serv a t iv e in d ica t io n of S192

capabil i t ies because of the so mewh a t u n so p h is t i ca tedclass ificat ion a lgo r i thm used and the l i m i t e d n u m b e r o fcategories an d ban d co mbin a t io n s av a i l ab le ."

Most of the in v es t ig a t io n s th a t in c lu d ed co mp u te r -a ided analysis of SI 92 data w ere involved with test areashaving l i t t le topographic rel ief . In contras t , a s tudy byHoffer (ref. 2-5) involved a 77 354-hm 2

test site in the

S an J u a n M o u n t a i n s of southwestern Colorado—an




area of rugged topographic relief and complex pa t t e rnsof cover types. This study site was in a pa r t i cu l a r ly im -p o r t a n t region from th e s t a ndpo i n t of many c onf l i c t ingdemands for use of the land; e .g. , t imber product ion,wild l i fe habi ta t , grazing, recreat ion, and mineral pro-duc t ion . Increas ing publ ic pressure fo r s um m e r - andpermanen t -home deve lopments i s caus ing much con-cern on the pa r t of the U.S. Forest Service, th e N a t i ona lPark Service, the Bureau of Reclamation, and otheragencies responsible for mana geme nt of these lands. Asa result of this pressure, personnel from these agenciesindicated considerable interes t in obtaining reasonablyaccurate and up-to-date cover-type maps that could beused fo r inventory purposes and for monitoring en-v i r o n m e n t a l al tera t ions .

Computer class if icat ion of the S192 data involvedseveral differen t ana lysis sequences. First , a detaileds tudy of the data q ual i ty indicated considerable varia-tion among the 13 wavelength bands , from both aqual i ta t ive and a quant i ta t ive s tandpoint . A newly

developed "modified clus tering" technique (discussedin sec. 6) was used to obtain t ra ining s ta t is t ics . Adivergence a lgori thm w as used to de te rmine the op-t imum combinat ion of wavelength bands for variousnum b e r s of bands , and the best four bands were iden-tified as 0.46 to 0.51, 0.78 to 0.88, 1.09 to 1.19, an d 1.55to 1.75 /xm. The data were classified by using a max-imum -l ikel iho od a lgori thm . The cover types involvedin this phase of the analysis were coniferous forest,deciduous forest, grassland, exposed rock and soil,water , and snow. Figure 2-12(a) il lustrates th e compute rclassification map of major land use classes for a sampleportion of the entire test area as compared to a cover-

type map (f ig. 2-12(b)) developed by manual interpreta-t ion of the aerial photographs that were obtained in sup-por t of this S kylab miss ion. The figure shows that thesetwo maps qual i ta t ive ly compare qui te wel l .

To obtain a quant i ta t ive evaluat ion of this classifica-tion of land us e cover types, a test area consisting of astatistically defined grid of four by four resolution ele-m e nts w as used. A summary of class if icat ion perfor-m a nc e for each la nd use class is sho wn in table 2-VIII.In this case, th e overall classification accuracy was 85percent . If the coniferous forest and the deciduousforest were combined, the overall accuracy for forestcover w ould be 98 per cen t. Several other in vestigato rsalso indicated that forest cover, as a major cover type,

could be accura te ly mapped . The grassland category w asth e most diff icu l t to classify; i .e. , a cons ide rab le amoun tof grassland was misclassified as deciduous forest.Hoffer bel ieved that this misclass if icat ion occurred pri -mari ly because foliation of much of the deciduousforest cover was not complete at the time of the Sky la b

2 overpass (June 5, 1973). Therefore, th e tra ining fieldstatistics for grassland tended to overlap those ofdeciduous fores t . The cover-type category of "exposedrock and soil" is not included in table 2-VIII becausenone of the statistical-grid test areas fell on a suffi-

ciently large area (a pp rox ima tely 8 hm2

minimum s ize )of exposed rock or soil .

Evaluat ion of the computer-developed classificationmaps indicated that th e classification w as reasonablyaccurate , and an estimate of the areal extent of eachcover typ e was then tabulated ( table 2-IX). This tabula-tion required 45 seconds of com pute r tim e to com pletethe entire 77 354-hm

2area.

Areal estimates of the major cover types obtained by

pho tointerpreta t ion were compared, on a quadrangle-by-quadrangle bas is , to the areal summary based oncomputer-a ided analys is of EREP data . This com-parison resulted in a correlation coefficient of 0.929.Hoffer (ref. 2-5) stated that this correlation w as par t i cu-larly significant because it indicated (together withsimi lar results obtained from Landsat-1) that reliableareal estimates can be obtained by using computer-aided analysis of satellite data, even for areas of ruggedmountainous terrain. It was also noted that, for arealestimates obtained from computer classifications, com-mission and omission classification errors tended tobalance, part icularly as the geographic areas involved

became larger. A s imilar c o m m e n t concerning suchareal estimates was made by Sattinger et al . (ref. 2-18).Urban land use mapping with use of SI 92 thermal -

infrared data.—Although relatively fe w detai led urban-mapping s tudies with S192 data were undertaken,several investigators concentrated their efforts on thevalue of the therm al-infrared band because i t provided at ype of data that could not be obtained with the higherresolu t ion EREP photographic systems.

The th ermal- infrared band and a densi ty-s l icing tech-n i q u e were used by Hannah et al . (ref. 2-2) to mapOrlando, Florida . Th e resul tant thermal m ap indicatedthat the thermal radiance is highest for commercia l - in-dust r ial regions, next highest for "mode rn" residential




W hi te Snow R edBlue W a t er Brown

Dark green Coniferous forest Y el low

Light green D eciduous forest

E xplanat ion

G rasslandExposed rock an d soil

M i x ed Scale, km

FIGURE 2-12.—Comparison between major cover types obta ined by c o m p u t e r c l a s s i f i c a t i on of S192 data (fig. 2 - 1 2 ( a ) I an d those obta ined b y

manual in terpreta t ion of aeria l ph otographs (f ig . 2-12 (b ) ) of the Va l leci to Reservoir s tudy area in southwestern Colorado. Th e reservoir is at the

t op . (a ) Computer classi f ica t ion , (b ) M a n u a l i n t e rp re t a t i o n .

a reas h av in g r e la t iv e ly fe w trees, and less fo r mo re

wooded res identia l areas. The co mmerc ia l - in d u s t r ia lsectors were identif ied and en h an ced by c o m p u t e r -

a ided analysis of the th e rma l - in f r a r ed d a ta . In this

geographical area , even th e "modern" res identia l and

wooded res identia l areas were d i s t in c t ly d ef in ed by thisd en s i ty - s l i c in g tech n iqu e . H an n ah co n c lu d ed th a t th i st y p e of "a th e rma l r ad ian ce m ap m i g h t be used to

classify sectors acco rd in g to t h e i r e n v i r o n m e n t a l im -pacts (rela t ive to a m o u n t s of trees and other vegetat ion

an d co n cre te ) an d ce r ta in ly can be ut i l ized by p lan n er sas a graphic indication of the value of landscaping ."

Alexa n d er an d L in s ( r e f . 2 -1 1 ) s tu d ied th e S kylab

SI 92 thermal- inf rared data as a source of informationo n u rban c l ima tes an d su r f ace en erg y ba lan ce in u r -banized areas . In their exper iment, a combination of




T A B L E 2-V1H.—Classification Performa nce for Major Cover Types Using Four

Wavelength Bands a ofSkylab S192 D a t a Obtained on June 5, 1973

Cover-type

category

W a t e rSnow

GrasslandDeciduous fores t

Coni fe rous forest

Totals

No . of

samples

96

1 1 2

128

36816%

2400

No. of test-area samples classified as —

Water

91

000

0

91

Snow

0112

002

11 4

Grassland

00

67

01

68

Deciduous

forest

00

2822 7

132

387

Coniferous

forest

5

033

132

1542

1 7 1 2

Rock/soil

0009

19

28

Percent

classified

correctly

94.8

100.0

52.3

6 1 . 7

90.9

"85

aBands 2. 7. 9. and 11 (opt imum four).

"Over a l l per for mance (2039 /2400) - 85 .0 per cent .

mo d el in g and observational techniques w as used toassess th e ap p l ica t io n of r emo te sensors to i m p r o v e un-ders tanding of the rela t ionships between surface prop-

erties and the mesoclimates of urbanized reg ions .Because dras t ic changes in land use, such as land clear -

in g and u rban iza t io n , o f ten h av e a s ig n i f ican t c l im a t ic

i m p a c t on urbanize d areas , th is s tudy w as u n d e r t a k e n tod er iv e in f o rmat io n u sef u l fo r land use p lan n er s who arer equ i r ed to consider energy use and c l ima to lo g ica leffects of proposed changes in th e i r p lan n in g ju r i sd ic -

tions.

T A B L E 2-IX.—Area! Estimates for Major Cover Types

in the Colorado Granite Peaks Test Site Based onComputer Classifications of Skylab SI 92 Data

Cover-type category

W a t e rSnow

Grass landConi f e rous forest

Deciduous fores t

Expo sed rock an d soil

Totals

No . of scanner

resolution

elements

20641 6 8 5 2

3 3 9 7

109 975

3 1 370

2 8 6 5

166 523

Area , hm:

95 9

7 8 2 8

1 5 7 8

5 1 086

1 4 5 7 2

1 331

7 7 3 5 4

The c l i m a t e of an urbanized reg ion has been d e-scr ibed s im p l i s t i c a l l y as a group of heat islands set in am a t r i x of co o le r , n o n u rban a r eas . Th e s t u d y of such

heat is lands clear ly involves m o r e th an th e an a lys i s ofth e su r f ace th e rm a l s ta te. The o v era l l r e f lec tan ce of anarea wi l l co n t ro l th e amo u n t o f en erg y be in g abso rbed

by the surface and thus affect t h e n e t r a d i a t i o n , w h i c h i sth e ba lan ce be tween en erg y abso rbed an d en erg y emi t -ted . I f one is l im ited to the use of ground-based data co l-

l ec t io n tech n iqu es , effec t ive an d accu ra te n e t r ad ia t io n

measu remen ts o v er differen t lo ca t io n s an d co n d i t io n s

are e x t r e m e l y di ff i cu l t to o bta in . Th e S I9 2 scan n ersystem, however , p rovided an ef fective method for ob-

t a in ing a broad v ar i e ty of data on cover typ es and cond i-tions. The 10.2- to 12.5-/xm ban d was ca l ib r a ted by u s in g

a var iety of reference data to correct for a tmospher iceffects . A l e x a n d e r a nd L i n s (ref . 2-11) then generated a

m ap th a t sh o wed th e d i s t r i b u t i o n o f su r f ace - r ad ia t io ntemp era tu r es in th e Ba l t im o re , M ary lan d , a r ea f o r th e

Au g u s t 5 , 1973, S kyl ab o v erp ass ( f ig . 2 -1 3(b ) ) . The cor-

responding por t ion of an S190B photograph (f ig .

2-13(a)) is s h o w n fo r co mp ar i so n . Th e r ad ia t io n - tem-p era tu r e m ap sh o ws th e v a lu e of the s y n o p t i c v i e w ob -t a in ed f ro m sp acecr a f t a l t i tu d es fo r th i s typ e of s t u d y .

Th e h yp o th es ized u rban heat is lan ds are eas i ly ide n-

t ified o n th e map , an d th e r e la t iv e co o ln ess o f n o n u rb an

land is effec t ively d o c u m e n t e d . T h e r m a l p a t t e r n s a n dabsolu te values of r ad i a t i o n levels were obtained , docu-m e n t e d , and l a ter used to test th e s i m u l a t e d m o d e l of




•

L e v e l

S u r f a c e r a d i a t i o n

t e m p e r a t u r e , K (°C)

2 9 8 3 0 1 3 0 4 3 0 7

(25) (28) (31) (34)

N o . o f c e l l s

1237 4121 2748

1 2 3

« * • » » • + + • X X X X X X X X X

1277

4

899999989 8

989999989 69898 9899 8

999998989 8

989999998 8

310 313

(37) (40)

37 2 16 8

5 6

e e e s e e e e i i i i i i n ii i i i i n i i

e e e e e a e 1111 1 1 1 199889988 Illllllll

86989980 Illllllll

L e v e l

(cl

A b s o l u t e v a l u e r a n g e a p p l y i n g to e a c h l e v e l( m a x i m u m i n c l u d e d in h i g h e s t l e v e l o n l y )

M i n i m u m s u r f a c e r a d i a t i o n t e m p e r a t u r e , K (°C)

293.15 295.98 298.82 301.65 304.48 307.32( 2 0 . 0 0 ) ( 2 2 . 8 3 ) ( 2 5 . 6 7 ) ( 2 8 . 5 0 ) ( 3 1. 3 3 ) ( 3 4 . 1 7 )

M a x i m u m s u r f a c e ra d i a t io n t e m p e r a t u r e , K (°CI

295.98 298.82 301.65 304.48 307.32 310.15( 2 2 . 8 3 ) ( 2 5 . 6 7 ) ( 2 8 . 5 0 ) ( 3 1 . 3 3 ) ( 3 4 . 1 7 ) ( 3 7 . 0 0 )

1 2 3 4 5 6

• •• • X X X X X X X X X 898888888 888888888 Illllllll..... X X X X X X X X X 888999989 1188888888 Illllllll

• X X X X X X X X 8999 9999 8888 BB88 Illl Illl....... X X X X X X X X X 898998989 B B B B B B B B B Illllllll

......... X X X X X X X X X 899999999 BB 8 B 8 8 8 B B Illllllll

S c a l e , k m\

FIGURE 2-13.—An S190B photograph an d computer-generated

temperature maps of the Balt imore , M aryla nd , area. ChesapeakeB ay p ro t rud e s from the r igh t . The w hi te patches in the photog raph

ar e clouds . (Original scale , 1:250 000.) (a ) Small portion of anS190B photogra ph taken Au gust 5 , 1973, showing the surfacefeatures (SL3-83-166). (b ) Com p ut e r - ge ne ra t e d t h e rm al - i n f r a re d

s ur f ace - r ad i a t i on - t e m p e ra t u re m ap obtained from S192 data band13 . (c) C o m p u t e r - g e n e r a t e d , s i m u l a t e d s u r f a c e - r a d i a t i o n - t e m -

perature map.




the area ( f ig . 2-1 3(c) ) . These resul ts indicate the valueof such thermal - infrared data for observing the ac tualtemp eratu re character ist ics of an urban area, despi te thefact t h a t th e qu a l i t y of these pa r t i cu l a r t h e r m a l - i n f r a r e dda t a was less t han op t imal fo r t he t he rmal -mapp ing pur -poses. Alexa nder and L ins ( ref . 2-11 ) al so noted th at

th e conical scan pat tern of the S192 scanner system w asvery desi rable fo r th is type of work because it enablesmaintenance of an opt imal path of constant length forth e scanner data.

A s imul a t ion expe r imen t us ing th e t h e r m a l - m a p in -

fo rmat ion w as conducted on the basis of the concep tthat each land use type has a pa r t i cu l a r mix of surfacecover an d bu i l d ing conf igura t ion assoc i a t ed w i t h i t .

Therefore , i f a land use map wi th an appropriateclass if icat ion s c h em e i s avai lable , i t should be possib le

to use the d i s t r i b u t i o n of signif icant surface-covercharacter ist ics in model ing the energy balance and dis-t r ibu t io n . The surface character ist ics used by Alexander

and Lins ( ref . 2-11) as i n p u t for the energy balancemodel s tudies w ere (1) the bui lding con figura t ion,w h i c h provides i nfo rm at i on re lated to the surfaceroughness and solar radiat ion calculat ions; (2) the sur-face "wet f r ac t io n"; (3 ) the s u b s t r a t e t h e r m a l

diffusiv i ty and co nd uct ivi ty ; (4) the surface albedo; and(5 ) th e surface emissivi ty . The values of these factorsfo r each di ffere nt land use category were calculated and

used as i n p u t to the model on the basis of the l and usem ap of the test area.

A compar ison of the S192-derived and the simulatedsurface-temperature m a p s (figs. 2-13(b) and 2-13(c) ,respectively) show s that th e general heat dist r ibut ionw i t h i n th e city of Bal t imore is s imi lar to that of ou t ly i ngresidential and commerc i a l areas. Although both mapsshow th e same general ized pat terns of temperature dis-t r ibu t io n , differences are apparen t in the shape of in-d iv id u a l features. The map obtained from th e S192 datah as much m or e compl ex and in t r icate pat ter ns thanthose on the simulated map. Also, th e simulated m aptemperatures are as much as 6 to 8 K lower than th etemperatures on the S192 map for the area in the centerof the c i ty heat i s land. Alexander and Lins stated thatthere i s a considerable potent ial for fur ther improve-

m e nts in simulat ion-map studies through the use ofsuch thermal - infrared scanner data. The results also in -dicated that th e input f rom th e l and use map used fo r

th e s imul a t ion model did not have sufficient detail con-cerning p h e n o m e n a tha t affect surface temp erature.

The l and use classes mapped in the s imul a t ion s tudytend to general ize ma ny features such as houses , streets,

lawn s, forests , and f ie lds.Al though th e re su l t s of the SI92 da t a ana l ys i s

showed a po t en t i a l u rban app l i ca t ion o f a s imul a t ed su r -f ace - r ad ia t io n - temp era tu r e map , the inves t igat ion indi -

cated a need fo r fu r the r de f in i ti on of those phenomenathat affect surface temperature . In essence, the land usecategories mapped may not represent the dist r ibut ion ofthe features that ac tual ly affect the surface- temperatureregime or the su r face -ene rgy -exchange phenomenonw i t h suff ic ient r ea l ism . Con sequen t l y , th e invest igatorsrecom mend fur th er work to ref ine and develop a moredetailed cla ssifica tion for land cover th at can be effec-

t ively used fo r cl imatological purposes.An integral par t of the land use inv est iga t ion by Silva

(ref. 2-14) over an area in northeastern Indiana was thean a lys i s of S192 data obtained on January 25, 1974, forth e city of For t Wayne , Ind i ana . The l and use classes in -

volved were resident ial , commercial - indust r ial , h a r dsu r face s (park ing lots and runways) , grass-coveredareas (pastures, winter wheat , and golf courses), bareland, forest /snow, water , and snow. The analysis pro-cedures Silva used were basical ly th e same as those dis-cussed in the preceding subsect ion. The classi f icat ionperform ance of the scanner reso lut ion e lements, or pix-els, used to t rain the com puter i s show n in table 2-X.Th e op t imum combina t ion cons i s t s of four wavelengthbands—one band in the visib le wavelength region(band 4, 0.56 to 0.61 ^.m), one in the near infrared(band 8, 0.98 to 1.08 f j . m ) , one in the middle infrared(band 1 1 , 1.55 to 1.75 /im), and one in the t h e r m a l in -frared (band 13, 10.2 to 12.5 //.m). This combinat ionresulted in an overal l t ra ining -p ixe l c lassi f icat ion per-fo rmance of 90 percent . W h e n th e t he rmal - in f ra redband w as excluded, th e accuracy of the s a m e t r a in ingpixels decreased to 80 percent. W h e n th e midd l e - in -frared band w as exc l uded , a visib le band ( the only oneavai lable in this data set) , tw o near- infrared bands, andth e t he rmal - in f ra red band were selected fo r use; and theresul tant c lassi f icat ion performance was 79 percent .This comparison indicates th e value of both th e ther-ma l - in f ra red and t he m idd l e - in f ra red wave l eng th bandsin th is land use classi f icat ion sequence. One of the mosts ignif icant results is seen in the extremely poorclassification p e r f o r m a n c e (even for the t ra inin g data)

of the resident ial and commerc i a l - i ndus t r i a l l and useclasses w hen the the rma l - infr ared waveleng th band is




TABLE 2-X.—Training-PixelClassification Performance

Land us e No. of

pixels Optimum four bands

R es iden t i a l

C o mmer c ia l - in du s t r i a l

Ha r d s ur f ace

GrassBare l andFores t /snow

W a t e rSnow

17 5

• :5 2

14 1459

8 1

15 225

overall

(4, 8, 11, 13)

9295

7 3909S

7 9M l

96

Overal l pe rfo rm a n ce M146 90

aTola l n u m b e r of u a i n i n g pixe l s .

not used. These t wo u r b a nfo r most of the decrease into 80 pe rc ent .

The i m p o r t a n c e of theb a nd in d i s c r i m i n a t i n g th e

classes alone w o u l d a c c oun toveral l p e r f o r m a n c e from 90

thermal - infrared wa ve l e ng t hu r b a n land use classes from

th e other cover types is s h o w n in figure 2-14. In thesewin te r t ime SI 92 da ta , th e c om m e r c i a l and industr ia l

Percent classified correctly

Optimum four bands

exclusive of thermal

infrared (4, 7, 8, 11)

6 5

•71g g

93S I ,

77

92

80

Optimum four bands

exclusive of middle

infrared (4, 8, 9. 13)

(29 0

5 2M

J9-4

5 8

9 2

7 9

T r a i n i n g classes

R e s i d e n t i a l

C o m m e r c i a l

I n d u s t r i a l

H a r d s u r f a c e

m m1 1 1 1 1

nL±.

f T T M l

E D

1 1

classes and , to a somew hat lesser exten t , the res ide nt ia lc l as s have eq uiva len t b l ack-bod y t emp era tures signifi-can t ly higher than those of the other land use classes.The effect of these paramete rs on de te rmining a rea pe r -centage of land use classes w i th S192 band s is show n in

table 2-X I. Co mp arin g the area es timates of the variousl and use classes obta ined by the c om pute r c l a s s if i ca tionover th e entire test site to the area es t imates developedby conv ent iona l metho ds used by c oun t y and city p l a n -n ing agencies offers a p r oc e du r e to es tabl ish th e qual i ty

of the results. Such a m e t hod w as pursued in th i s s tudyand was f ound to be especia l ly useful fo r s howi ng th evalue of the th e rma l - in f r a r ed b a nd in t h i s ana lys i s in -volving an urban a rea . Compar i son of the compute r -derived areal es t imates with those provided by thecoun ty and ci ty agencies for the five ma jor categories inthe data shows that the es t imates obtained by us ing theth e rma l - in f r a r ed da ta fo r b a nd 1 3 a p p r o x i m a t e th e esti-ma tes provided by the ci ty and the c oun t y . Th e

differences in the urban class can be explained, for themos t pa r t , by the di f fe rences in the cover types thatwere included in the urb an area . For ex am ple, cover

G r a s s

Bare land

F o r e s t / s n o w

W a te r

Snow

2 6 1 2 6 5 2 6 9 2 7 3 2 7 7 2 8 1 2 8 5 2 8 9( - 1 2 ) ( - 8 ) ( - 4 1 ( 0 1 ( 4 ) ( 8 ) ( 1 2 ) ( 1 6 1

Equiva lent temperature, K (°C)

FIGURE 2-14.—Equivalent black-body temperatures computedfrom the S192 therm al- infra red band for training classes. V alue s i n -

c lud e th e mean p lus o r m i n u s on e standard deviat ion. Mult ip le

classes are shown for bare land and water .

3 8 S K Y L A B E R E P I N V E S T IG A T I O N S S U M M A R Y



typ es su ch as golf courses and parks were class if ied , ac-c o r d i n g to the d a ta p ro v id ed by th e c o u n t y an d city

agencies , as urban area; bu t these cover types wereclassified as grass land in the c om pu t e r classification

an d th ere f o re g ro u p ed w i t h th e w i n t e r w h e a t a sag r i c u l tu ra l land . The area class if ied as snow was largely

agr icu l tural l an d . Th e u n d eres t im a te o f co m merc ia l an d

i n d u s t r i a l area was largely due to c lassi f icat ion er ro r ssu ch as th e r a i l r o ad r igh t -of -way th ro u g h Fo rt W ayn e ;th e r i g h t -o f -way was co n s id er ed a s co mmerc ia l in th e

es t ima tes p ro v id ed by th e city but was class if ied by theco m p u te r a s ba r e soi l . Also , th e A l len Co u n t y P la n n in gCo m miss io n es t ima tes f o r th e in d u s t r ia l an d co mm er -

cial c a t e g o ry i n c l u d e d th e a reas o wn ed by businesses o rin d u s t r ies ( i . e ., bu i ld in g s , p a rk in g lo t s , an d l an d sc ap edp r o p e r t y ) . In th e co m p u te r c la s s i f ica t io n , th e bu i ld in g sth emse lv es were largely d e l in ea ted a s co mm erc ia l o r in -dus t r i a l and the crushed s tone lo ts as h ard su r f ace , orth e a sp h a l t p a r k i n g lo ts were of ten ident i f ied as be in gre s iden t i a l . These r esu l t s p ro v id e s o m e in s ig h t in to th e

c o m m e n t s by several of the in v es t ig a to r s th a t th e landuse classes designated by user groups or U S G S C i r c u l a r

671 (ref . 2-1) of ten may not co incide with the covertypes that can be spectrally discriminated by usingremotely sensed data .

As in table 2-X, th e v a lu e of the t h e r m a l - and mid d le -infrared wav elen g th s fo r accu ra te i d en t i f i c a t i o n of l an d

u se classes, pa r t i cu l a r l y th e urban classes , is s h o w n intab le 2-X I . Absen ce o f th e t he rma l - in f ra red ban d cau sesa v ery signif ican t ove rest i ma tion of the area in the ur -

b an category. W ith th e th e rma l - and middle- inf rared

ban d s p r esen t , th e a r ea l e s t ima tes o b ta in ed by co mp u te r

c lassi f icat ion c o m p a r e favorably with th o se o b ta in ed by

c o n v e n t i o n a l t e c h n i q u e s .Comparison of Skylab SI 92 and Landsat mult ispectra l

s c a nn e r an a l y se s .— S e v e r al i n v e s t i g a t o r s c o m p a r e d

c lassi f icat ion r esu l t s o b ta in ed by u s in g S kyl ab S192 andL a n d s a t d a ta . In essen t i a l l y every case, bo th Level I and

Leve l II l a n d use co v er typ es co u ld be m a p p e d w i t h ap -p r o x i m a t e l y th e same overal l degree of accu racy byus ing e i th e r th e Sky l a b or the Landsat data . In general ,th e in v es t ig a to r s f o u n d th a t th e wav e len g th ban d s

abo v e 1 .1 m , w h i c h w e r e a v a i l a b l e on the S k y l a b d a t abut not on the L andsat data , we re f r equ en t l y selected by

th e v ar io u s co mp u te r an a lys i s r o u t in es as being veryi m p o r t a n t and valua ble bands to use in the class ifica-

t ion . The d a ta q ua l i t y general ly w a s mu ch be t te r for the

Landsat data being used than for the S kylab d a ta . Th eresu l ts d id indicate that the improved spectra l reso lu-t io n av a i l ab le wi th th e S kyl ab S192 data enabled im -

provement in classification accuracy.

One of the mo re p r ec ise co mp ar i so n s be tweenclass if ica t ion r esu l t s o b ta in ed by u s in g th e S kyla b S I9 2data and the Landsat data was accomplished by Hoffer

T A B L E 2-XI.—Land U se Area Percentage Estimates fo r Major Portion of Allen County, Indiana

L a n d use category Area est imate, percent

( b )

U r b a n

R e s i d e n t i a l

C o m m e r c i a l - i n d u s t r i a l - h a r d s u r f a ce

A g r i cu l t u r a l / f o r e s t

Water

O t h e r l a n d

Snow

Local Allen Count

reference data »

12.6

( 1 0 . 1 )

(2.5)

85.6-

1 x—

i

Opt imum four

ba nd s overall

(4, 8, 11. 13)

9. 9(9 .1 )

( .8)85.6

1.4—

- !

Skylab 4 SI 92 data

Opt imum four

bands exclusive

of t hermal infrared

(4. 7, 8. 11)

27.7

(26 .7 )

(1.0)

68.1

1.4

—2.8

Opt imum four

bands exclusive

of middle infrared

(4. 8. 9. 13)

7. 3

(6.8)

(.5)87.3

1.6—

3.8

Data f rom th e Al l en C o u n t y P l a n n i n g C o m m i s s i o n and the Fort W a y n e D e p a r t m e n t of C o m m u n i t y D e v e l o p m e n t an d Pl anning.

^Va lues in parentheses ar e s u b t o t a l s .




( ref . 2-5 ) . Fo r th is ef for t , a f r a m e of Lan d sa t d a ta w asused t h a t had been dig i ta l ly registered to bo th th e S192

data and to a USGS 7 .5 ' quadrangle m ap base w i t h areasonably high degree of precis ion (±1 p ixe l ) . Th eSk y lab SI 92 and Landsat data were obtained on thesame d a y ( w i t h i n 2.5 h o u r s ) an d u n d er co mp le te ly

cloud-f ree co n d i t io n s . S ta t i s t i ca l ly d ef in ed g r id s o f th etest area (each, four by f o u r p ixe l s in size) were used toev a lu a te th e class if icat ion resu l ts so that they could beq ua n t i t a t ive ly co mp ared fo r exac t ly th e s a m e reso lu tion

e lemen ts on the g ro u n d wi th use of the d i f f e ren t data

sets.

T h r ee class if icat ions were conducted . Firs t , t he ma-jo r cover types present in the area were classified byusing th e f o u r o p t imu m wav e len g th ban d s of S k y l a bS192 data (bands 2, 7, 9, and 11, as d e te rmin ed by thed i v e r g e nc e a l g o r i t h m ) . S e c o n d , t h e f o u r S 1 9 2wav e len g th ban d s th a t m o s t closely corresponded to thefour Landsat bands (bands 3, 5, 6, and 8) were used to

c la s s i f y t h e d a t a . T h i r d , t h e L a n d s a t d a t a w e r eclassified.

Silva (ref. 2-14) follow ed a v ery s im i la r p ro ced u re fo r

com par in g Sky lab S192 and Land sat data obtained over

a test site in cen t r a l I n d ian a . In his s t u d y , th e Lan d sa t

data were obtained a day before th e Sky lab data w ere

o bta in ed , and the two data sets were no t digi ta l ly

reg is tered . The tes t blocks for S ilva 's s tudy involved

hand-selected test areas ra ther than a sta t i s t ical lyde f ined g r id . T h e basic approach was t he same ,a l though t h e o p t i m u m f o u r S kyl ab bands used by the

au th o r s were d i f f e r en t .Th e overal l resu l ts of these tw o l an d use s tudies are

s h o w n in tab le 2 -XI I . Th e f o ur o p t i m u m c o m b i n a t i o n sof wa velen gth bands f rom Sky lab data produc edclassification resu l ts tha t were a lmost identic al in both

investigations . In both s tudies , the four w a v e l e n g t hban d s of S k y l a b da ta th a t most closely corresponded toth e Landsat bands produced less accurate resu l ts than

those o bta in ed u s in g th e ac tu a l Lan d sa t d a ta . C o n s id er-

in g that the cover types were ra ther d i f f e ren t in the two

test locations , i t is s ignif icant that the resu l ts of bothco mp ar i so n s a re a p p r o x i m a t e l y th e same. The Colorado

T A B L E 2-XII.—Comparison of Classification Performances UsingSkylab and Landsat Multispectral Scanner Data

Data W avelength bands used Overall classification performance, percent

Hoffer's resultsa

(ref. 2-5)

Silva's resultsb

(ref. 2-14)

O p t i m u m four waveleng th bandsof Sky lab da ta

Skylab da ta us ing waveleng thbands that correspond to L a n d s a t

Landsat data

0.46 to 0.51,0.78 to 0.88,1.09 to 1.19, an d 1.55 to 1.75 M m'(bands 2, 7, 9, and 11)

0.52 to 0.56, 0.62 to 0.67, 0.68 to 0.76,and 0.98 to 1.08 pim (bands 3, 5,6, and 8)

0.5 to 0.6,0.6 to 0.7, 0.7 to 0.8,and 0.8 to 1.1 pm (band s 4, 5, 6,and 7)

85.0

82.5

85.7

*-

•>

-

aCover types were coniferous forest, deciduous forest, grassland, wate r, and snow .

"Cover types were res ident ia l , comm erc ia l - indust r ia l , ex t rac t ive , soi l, grass, dec iduous fores t , coniferous fores t , r ive r , and lake .

cFor Silva's data, th e o p t i m u m c o m b i n a t i o n of four wavelength bands inc luded th e 0.52-to0 .56-j im b a n d (3 ) r a t h e r t h a n th e 0.46-to 0.5 l -* im band (2) , and the 0.98-to 1.08-^m b a n d (8 )r a the r than th e 1.09- to 1 .19 -^m band (9 ) . In both cases, these bands ar e ad jacent to those used by Hoffer Th e other tw o bands were i dent i ca l in both s tud ies .




si te (Hoffer , ref . 2-5) invo lved comp lex mou ntaino ust e r ra in cons i s t i ng p r i m a r i l y of forest and rangelandcover types, whereas the Ind ian a test s i te (S i lva , ref.2-14) involved urban and agricul tural cover types.

Both invest igators concluded that the be t ter spect ralresolut ion and the extended spect ral range of the Skyla b

S 1 9 2 s c a n n e r c o n t r i b u t e d t o a n i m p r o v e m e n t inclass if ica t ion pe r fo rmance . Th i s improvement w as ind i -cated by the difference in the classification results ob-tained by using the best four wavelengths that corre-sponded to the Landsat scanner systems. The fact thatth e Sky l ab da t a did not yie ld bet ter c lassi f icat ion resul tsthan th e Lan dsat da ta was at t r ibu ted to the noisych a rac te r i s t i cs of the Sky l ab da t a . Th e invest igatorsbel ieved that the resul ts obtained indicated the impor-tance of good-qua l i t y da t a , th e value of using the op-t imum combina t ion o f fairly narrow, proper ly locatedspectra l bands fo r cove r - t ype mapp ing , and the va l ue ofu s in g compute r -a ided ana l ys i s t e chn iques .

Polcyn et al . (ref. 2-17) also conducted a comparison

of Skylab and Landsat c lassi f icat ion resul ts , for a testsite in Ontar io , Canada. The percentage of the total areaclassified in to the var ious cover types by using fourS192 bands (bands 4, 5, 7, and 13; 0.56 to 0.61, 0.62 to0.67,0.78 to 0.88, an d 10.2 to 12.5 M m , respect ive ly) w ascompared wi th th e Landsat data c lassi f icat ion. Theresul ts indicated th at a reasonably si mi lar c lassi f icat ionwas obtained with both data sets. A detailed com-par ison wi th aer ial photographs indicated that bothSkylab and Landsat data had enabled achievement of areasonable c lassi f icat ion, wi th som e var i a t i on amongcategories w ith in both data sets. The most severemisclassi f icat ion occurred wi th th e Landsat data in the

manmade category of cover types. Overrecognition oc-curred, and, in general , th e bare soil category caused th em os t confusion. It was concluded that th e Skylab S192an d Landsat data appeared to be reasonably equivalentin t e rms of i n fo rmat ion con ten t and dist inct ion of thevarious cover types in the area involved. Most of thedif ference in the percentage of the area recognized aspart icular classes can be accounted for by differences inthe training-set signatures used rather than by any fun-dam ental di fferen ce in the inform at ion content in thespectral data from the scanner system.

Cover - type maps of the Green Swamp area inFlorida were generated with the use of both Landsat

and Skylab S192 data (Higer et al . , ref. 2-16). The result-in g classi f icat ions were representat ive of the cover

types present , and the vegetat ion maps produced fromSI92 and Landsat categorized data were in accord wi thcounty land use maps by 82.8 and 87.2 percent , respec-tively. Hannah et al. (ref. 2-2) stated that computerclass if ica t ion of S192 data over an urb an area (O rlando,Flor ida) resul ted in cover- type maps that were of

general ly comparab l e qual i ty to those previously ob -tained from Landsat .To summar i ze , th e compar i son of Sky l ab and L a n d -

sat c lassi ficat ion resul ts showed that the increased num -ber of spect ral bands of the Skyla b scan ner systemenabled de f in i t ion of a be t ter combinat ion of fourwavelength bands fo r compute r ana l ys i s .

W a v el en g th b a n d e v a l u a t i o n . — D e t a i l e d i n v e s t i g a -tions were conducted to d e t e r m i n e th e combina t ions ofwavelength bands that are opt imum for land use map-ping . This subsect ion is a br ief summary of some ofthese resul ts . The reports by Hoffer , Si lva, and Simonet t(refs. 2-5, 2-14, and 2-10, respectively) are pa r t i cu l a r ly

detailed on this subject.

In the in i t ia l phases of Hoffer 's investigation of theuse of S192 data in mounta inous t e r r a in , d i f f e ren t ap -proaches and tech niques were appl ied to def ine the dataquality of the different bands. These analyses resultedin a num erical data -qu al i ty index for each wav elengthband (table 2- XII I ) . To inter pre t the num erical values, aquan t i t a t i ve eva l ua t ion de s igna t ion was also defined.Comp arison of the data- qual i ty indexes w i th the imag-ery of the ind iv idua l wavelength bands s h o w ed t ha t , inseveral cases, th e visual appearance of the imagery orthe qu al i tat ive evaluat ion ( table 2-XII I) was not a re l i -able indicat ion of the spect ral informat ion content of

th e data. The invest igators stated t h a t th e qual i t y of

mult ispect ral scanner data can be effect ive ly evaluatedon l y b y quant i tat ive evalua t ion techniques ( rather thanqu a l i ta t iv e techniq ues) i f the data are to be analy zed bycompute r .

Anothe r phase of Hoffer 's investigation (ref. 2-5)w as directed to d e t e r m i n i n g th e n u m b e r of wavelength

b a nds required fo r effective classification with use ofth e S192 data. Previous work has indicated that, as then u m b er of wavelength bands increases, th e classifica-t ion performance i n i t i a l l y increases r ap id l y when fourto six wavelength bands are used but increases at aslower rate above this number . The a m o u n t of com-puter t ime required to classify the data increases signifi-

can t ly fo r m o r e than four to six bands , as shown infigure 2-15. The effect of increasing the number of

L A N D U S E A N D C A R T O G R A P H Y 41



Vis ib le

N e a r infra red

M i d d l e infra red

T h e r m a l

i n f r a r ed

T A B L E 2-XIII.—Data-Qu ality Evalua tion Results

[From ref. 2 - 5 ]

Spectral Band no . W avelength Quali tat ive Quan titat ive Qu antitat iv e

region band , pm evaluation data-quali ty evaluation

designation index designation

:I

4

•

•

-

-

•

:

: l

0.41 to 0.46

0.46 to 0.51

0.52 to 0.56

0.56 to 0.61

0.62 to 0.67

0.68 to 0.76

0.78 to 0.880.98 to 1.08

1.09 to 1.19

1.20 to 1.30

1.55 to 1.75

2.10 to 2.35

10.2 to 12.5

V ery p oor

Poor

V ery good

Poor

Fair

Fai r

V e r y good

Very good

V ery good

Good

V ery good

Good

Poor

7 I

:•

14.8

12.1

-

5.6; -

2.9

11.8

Fa ir

Good

V e r y goodPoor

Poor

Fair

Good

Fair

V e r y good

Fair

V e r y good

Good

Poor

w a v e l e n g t h bands on performance resul ts was tested onthe S192 data. The d ivergence alg ori th m was used tode t e rmine t he op t im um com bina t ion o f 1 t o 13wav elen g th band s. The d ata w ere then c lassi f ied byu s in g t he ma ximu m- l ike l i hood a l gor i thm . The re sul tso f th is analysis ind icated that c las si f icat ion perfo r-

mance was no t s ignif icant ly improved when more t hanfour wave l eng th bands we re used (fig. 2-16). These

r esu l t s were based on test-area c lassi f icat ion perfor-mance for both major and forest cover types. The over-al l classi f icat ion accuracy for the major cove r t ypes as a

fu n c t io n of the n u m b e r o f wave l eng th bands is s h o w nin table 2-XIV. For this data set, th e 1.09- to 1.19-jum

wav elen g th band in the near infrared was t he singlemost val uab l e wave l eng th band . Th e best com bina t iono f four wave l eng th ban ds cons i s t s of one in the visib leregion (the 0.46- to 0.51-Mm b a n d , w h i c h , in table 2-

XI I I , was indicated to be v i sua l l y o f qu a l i t a t i v e l y poordata q ua l i ty) , two in the nea r- infrare d region ( the 0 .78-

to 0.88-Mm and 1.09- to 1.19-M-m bands) , and one in themid d le - in f r a r ed region (1.55 to 1.75 M m ) - The best

c o m b i n a t i o n of six wavelength bands consists of two in

th e visib le , two in th e near i n f ra red , one in the m i d d l einf rared , an d o n e in th e t h e r m a l in f ra red . F u r t h e r m o r e ,de t a il ed s tud i e s i nd i ca t ed t ha t var ious combina t ions o ffour wave l eng th bands we re r equ i red to ach ieve op t im alc l a s s i f i c a t i o n p e r f o r m a n c e fo r d i f f e r e n t i n d i v i d u a l

cover types. The near- infrared port ion of the spect rum(especial ly the 1.09- to 1.19-/u.m wave l eng th band) wass h o w n to be of par t i cu l a r va l ue fo r effect ive vegetat ionm a p p i n g . T h e r e l a t i ve impor t ance of the d i f fe ren tspect ral regions an d th e i n d iv id u a l wave l eng th bandsvar ied signif ican t ly as a func t ion of the cover types to

b e m a p p e d .S i m o n e t t (ref. 2-10), using a series of stat i s t ical pro-

c e d u r e s , a l s o f o u n d that th e 1.09- to 1.19-^.mwav elen g th b a n d was th e most valua ble single band fo rd isc r imin a t in g among land use categories. For overal lland use m a p p i n g , in orde r o f r a n k i n g , th e most useful

si x spect ral bands were band 9 (1 .09 to 1 .19 pim ) , band 3

(0.52 to 0.56 M m ), band 6 (0 .68 to 0 .76 M m ), band 1(0.41 to 0.46 M m ) , band 1 1 (1.55 to 1 .75 M m ) , an d b a n d

4 2 S K Y L A B E R E P I N V E S TI G A T IO N S S U M M A R Y





TABLE 2-XIV.—Optimal W avelength Bands for M ajor-Cover-Type Classification UsingSky ab SI 92 Data Obtained on June 5, 1973

Spectral

region

Visible

N e a r inf rared

M i d d le inf rared

Band

:

4

•

•--

•

1 1:

W avelength

band,

i' "'•

0.41 to 0.460.46 to 0.510.52 to 0.560.56 to 0.610.62 to 0.67

0.68 to 0.760.78 to 0.880.98 to 1.081.09 to 1.191.20 to 1.30

1.55 to 1.752.10 to 2.35

Data-

quality

index

7.1

:1.8

14.8

12.1

4

• •

-

•

2.9

Opt imum wavelength-band combinations a

1 2 3 4

X X X

X X

X X X X

\

\

\

\

\

X

6

\

\

\

\

\

'

\

\

\

\

\

\

s\

X

\

\

X

X\

10

\\\X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

T h e r m a l inf rared 13 10.20 to 12.50

Overal l c lass i f i cat ion performance , perc en t

X X X X X

75.7 76.8 81.9 85.0 84.1 83.7 85.3 84.1 85.2 86.0

aB an d 9 was selected as Ihe single best wavelength b an d , b an d s 9 and 2 were selected as the two best wavelength bands , etc

TABLE 2-XV.—O ptimum Combinations of W avelengthBands for Mapping L a n d Use in Indiana

[Skylab 2 data]

No. of bands Bands of opt imum value a

Interim data set Filtered data set

,3

-

56

11

1 , 2 , 11

3 , 7 , 9 , 1 12 , 3 , 7 , 9 , 1 12 , 3 , 7 , 9 , 1 0 , 1 1

11

1 , 2 , 1 1

2 , 7 , 8 , 1 12 , 7 , 8 , 9 , 1 12 , 7 , 8 , 9 , 1 0 , '

aBand 13 was not available in the in te r im data set. an d b an d s 4. 5, 6. and 12 were no t

available in the fil tered data se t

The resul ts reported by Silva ( ref . 2 -14) (and pa r t l y

s u m m a r i z e d in t a b l e 2 - X I) dem ons t ra te the va lue o f thet h e rm al - an d m id d l e - in f r a red w a v e l e n g t h s fo r o b t a i n i n g

a ccura te a rea l e s t ima te s of the u r b a n l a n d u se class (pa r-t i cu la r ly t he re s iden t i a l ) . The S192 da ta ha d been ob -

t a in ed d u r i n g th e w i n t e r w h e n s o m e s n o w w a s on theg r o u n d . In this a rea , th e o p t i m u m c o m b i n a t i o n o f four

w a ve leng th ba nds (4 , 8 ,1 1 , a nd 13 ) re s u l t ed in a n a rea l

e s t ima te for the urban res ident ia l a rea of 15 000 h m 2 ,

com pa red to 16 900 hm 2 e s t im a t e d b y t h e F o rt W a y n e

D e p a r t m e n t o f D e v e l o p m e n t a n d P l a n n i n g . W h e n th et h e rm al - i n f r a red w a v e l e n g t h b a n d w a s n o t used, th ec lassi f icat ion resul ted in a res ident ia l a rea l es t imate of

43 85 0 h m 2 . W i t h o u t t h e m i d d l e - in f r a re d d a ta ( w h e n

us ing one v i s ib l e , tw o m idd le - in f ra red , a nd th e the rm a l -

infrared b a n d s ) , th e area l es t imate based o n th e c o m -

pu te r c l a s s i f i ca t ion was 11 200 h m 2 , compa red to

15 000 hm 2 w h e n all four major spectra l regions were

repre s en ted .

4 4 S K Y L A B E R E P IN V E S T I G A T I O N S S U M M A R Y



In th e Higer et al. s tu d y ( r e f . 2 -1 6 ) of the GreenS w a m p ( w h i c h in v o lv ed mo s t ly v eg e ta t io n , we t lan d s ,an d wa te r ca teg o r ies ) , th e f iv e wav e len g th ban d s th a t

p ro v id ed th e la rg es t co n t r ibu t io n to the ca teg o r iza t io nof the cover types present were, in o rd er o f p re f e r en ce ,ban d s 11, 8, 2, 10, and 6. Ban d 11 was p ar t i c u l a r l y im -

p o r t a n t for i den t i f y i ng v eg e ta t io n ; speci f ica l ly , Higer in -d ica ted th a t th e th e rm a l - in f r a r ed ban d w o u ld al so be

ve ry usefu l bu t t h a t , in th i s case, i t was excessivelynoisy. Thi s in v es t ig a to r n o ted th a t ban d s 8, 9, 10, and

11 , w hic h , except band 8 , are beyond the range of the

Landsat scanner system, were "usefu l in detection an dcategor ization of cover types in the Green S wamp ."

I n d i v i d u a l wavelength bands of S192 imagery ob-t a ined over several test sites in No r th Caro l in a were ex -

amine d by W elby and L am mi (ref . 2-13), us ing a den-

si ty-s l ic ing t ech n iq u e . Th e i r r esu l ts sh o wed th a t v a r io u svegetat ive cover types could be separated best by u s in g

th e n ea r - in f r a r ed wav e len g th ban d s , wh ich were a l so

fair ly effective fo r sep a ra t in g th e cropland areas f romfores t cover and in d ef in in g th e bo u n d ar ies be tweenvegetat ion an d water features .

A co lo r - ad d i t iv e v iewer was used by Welby an dL a m m i to com bine selected w aveleng th bands of theSI92 imagery. Their work showed that differen t co m-b i n a t i o n s o f w a v e l e n g t h b a n d s p r o d u c e d v a r i a b l eresu l ts in t e r m s of sp ec t r a l d i s c r imin a t io n of covertypes or land use categor ies . They concluded that work-in g w i t h c o m b i n a t i o ns of wav elen g th bands th rough useof th e color -addit ive v iewer w as m o r e effective thanan a lys i s o f in d iv id u a l wav e len g th ban d s an d th a t man y

of th e cover types present could be ef fectively separatedby u s in g th i s t ech n iqu e . A p ar t ic u la r ly imp o r tan t co n -clusion w as th a t " th e b r eak in g of the near - inf rared por -tion of the sp ec t ru m in to a series of r e la t iv e ly n a r ro w

bands appears to be a very usefu l approach to acqu is i -t ion of earth resource informat ion . "

W e l b y and Lammi id en t i f ied s om e of the co mp lex -i t ies encountered in a t temp t in g to man u a l ly in te rp r e tan d an a lyze man y in d iv id u a l wav e len g th ban d s o fm u l t i s p e c t r a l s c a n n e r i m a g e r y . T h e r e a r e m a n ywav e len g th ban d s to be considered , a nd d is t in c t

d if ferences in reflectance levels are of ten found in

d i f f e ren t wavelength bands in the same spectral region

(nea r inf rared , in th i s case) for the various cover typesof interest. These results also tended to emp h as ize th e

v a l u e of several d iscrete wavelength bands in the near -

i n f r a red p o r t i o n of the s p e c t r u m . If d i f f e r en ces in in-

f rared ref lectance among the cover types of in teres twere n o t p r esent in o n e wav e len g th ban d , an o th er ban dw o u l d en ab le e f f ec t iv e d i sc r im in a t io n .

To su mmar ize , th e wav e len g th -ban d ev a lu a t io n s

sh o wed th a t th e o p t imu m wav e len g th ban d s f o r e f f ec -t ive c lassi f icat ion of var ious land use cover types are th e1 .09- to 1 .19- /xm band in the nea r - inf ra red reg ion , the1.55- to 1 . 7 5 - / L i m b a n d in the mid d le - in f r a r ed r eg io n ,and the 10.2- to 12.5-£im ther ma l- in f rare d wav elengthband. Also , each of the four major spectra l reg ions (v is i-b le, n ea r in f r a r ed , mid d le i n f r a r ed , an d th e rm a l in -fra red) is s ignif icant with respect to accurate class if ica-

t ion , and the im por t anc e of each reg ion var ies as a func-t ion of the cover type and scene character is t ics .

En v i ro n men ta l Studies

Th e discussion on selected environmental s tudies in -c lu d es s t r ip min in g , we t lan d ma p p in g an d eco log y , an dmigra to ry water f o wl h ab i ta t ev a lu a t io n .

Strip m i n i n g . — I n c r e a s e d e n e r g y d e m a n d s h a v e

resu l ted in accelerated s tr ip -mining activ i t ies , the en-v ironm ental ef fects of whi ch are of increasing c oncern .

Estimates in 1970 of accum ulated coal prod uction (3992Tg) f rom str ip mining were s l ightly m o r e than 3 percent

of the total es t imate of strippable coal reserves (116 119Tg) in the Unite d S tates. Th e p o ten t ia l ly d i s tu rbed l an d

areas (those to be s t r i p m i n e d ) are estimated to exceedan area larger than th e combined s ize o f P e n n s y l v a n i aand W est V irg in ia . The p hotog raph in f igure 2-17 is an

exam p le o f s t r ip -min in g en d eav or s co v er in g an ex ten -s ive area in Alabama. On the basis of the growing pres-

sure to increase coal production , it is ap p a ren t th a t a

m o r e effective and efficient methodology will be re-quired t o map d is tu rbed min in g areas and to mo n i to rm i n i n g a n d reclamation activ i t ies .

Skylab ER EP in v es t ig a t io n s h av e p ro v id ed su bs tan -tial and posit ive ev idence that remote-sensing data ,specifically spacecraf t-acquired photographs , can be ofv a lu e in th e o v era l l p lan n in g , d e tec t io n , an d mo n i to r in g

o f su r face min in g ac t iv i tie s . Th e S kylab s t r ip -m in in g

studies are of two major types: (1) the detection andm a p p i n g o f dis turbed areas and (2) the id en t i f ica t io n




Black Warrior River

Forested area

•-, Strip-mined area ,

Bessemer, A labama,

UScale, km

FIGUR E 2-17.—A portion of an S190B color- infrared p hotograph i l lust ra t ing the extent of s t r ip-mining act iv i t ies in an area west of Bir-

m i n g ha m , A l a b a m a . The wel l -defined boundaries formed by the strip-mining operations and the natural vegetation should be noted. Tw o dis-

t inct ly dif ferent st ripping patterns are easily discerned (SL4-93-152).

46 S K Y L A B E R E P IN V E S T I G A T I O N S S U M M A R Y



and in terp re ta t ion of key ph ysic al features that arenecessary to m o n i t o r th e componen t s of ongoing st r ip-m i n i n g ope ra t ions an d r e c l ama t ion ac t iv i ti e s .

Th e s im p l i f i ed ph o to in t e rp re t a t i on t e chn ique usedby Brooks and Parra ( ref . 2-19) requires the use ofS190B 2x color posi t ive t ransparencies, an overhead

p ro jec to r , and a whi te poster board as the project ionscreen. I t enables mi ni ng officials who do not have ex-t ens ive pho to in t e rp re t a t i o n backgrounds or expens ives c a n n i n g e q u i p m e n t to out l ine , on the basis of colortones and dens i ty pa t t e rns , sa l ien t s t r i p -m in ing fea tu re s

(fig. 2-18).We i r et al. (ref. 2-20) have s h o w n t ha t a 1:100 000-

scale b lack-and-whi te S190B enlargement ( m a d e fromcolor fi lm) is satisfactory for accurately mapping pastand current surface mines and for de tect ing severalclasses of rec lamat ion assessment. Cul tural de tai l s atthis scale were adequate fo r preparat ion of new basem a p s or upda t ing ex i s t i ng topograph i c map s t ha t we re

enlarged from a 1:24 000 scale.Di s tu rbed s t r i p -min ing areas could be detected and

discr iminated on both S190A and S190B infrared photo-g raphs . For mon i tor ing surface min ing act ivi t ies , S190Bphotograph s, hav ing high spat ial resolut ion and spect rald i s c r i m i n a t i o n , prov ided th e m o r e detai led interpre ta-tion results for useful monitoring practices.

The Coshocton County , Ohio , S190B color-infraredphotographs were used by Baldr idge et al. (ref. 2-12) todef ine four major st r ip-m ining- land categories: (1) ac-

t ive areas, (2 ) o rphaned or abandoned l and , (3) areasundergoing rec lamat ion or restorat ion, and (4) natura lor plan ned rec laimed lands. The regrading of st r ip pin goperat ions was the most apparent feature observed onthe color- infrared images. Areas covered by va ryin gdegrees of vegetat ion, high wal l s , and wate r impound-m en t s were also identified. Baldridge et al . s tated thatland that h ad been thickly revegetated had the ap-pearance of be ing comple te ly rec laimed and wasdiff icu l t to ident ify as having been st r ipped. In someareas, high w al l s and pond water remained to indicatepast s t r ip pin g operat ions.

Table 2-XV I is a sum ma ry of key features ident i f iedby Baldridge, Brooks, and W eir (refs. 2-12, 2-19, and2-20, respectively). Their results i l lustrate the positivea t t r ibu tes of using S190B-type photographs. The three

invest igators used S190B enlargem ents to disc r imin atevar ious categories of mining ac t iv i ty and rec l amat ion(vegetat ion stages, refuse areas and s lurr y ponds, wa terbodies, high wal l s , haulage roads, unm ined areas,o r p h a n e d areas, and possib le ac id drainage effects) .

The most effective imagery scales for s t r ip -m inin g

and rec lamat ion act iv i t ies would encompass threeranges. The first range, 1:125000 to 1:250000, pro-vides a synopt ic overview of the general terrain andto p o g rap h y being mined. Over a per iod of t ime, thisrange would present a vivid pic tor ial history of exten-sive and evo l v ing pa t t e rns . The second range extendsfrom 1:62 500 to 1:100000. Two of the S ky lab experi -menters did most of the i r invest igat ive work w i t h i n t h i srange; specif ical ly , at the 1:80000 scale. Fo r more sub-tle details, scales rang ing from 1:24 000 to 1:50 000 arerequired. Th e S190B 2x posi t ive t ransparencies wereoptica l ly enlarged to achieve a usable 1:24 000-scale im -age.

Skylab photographs were al so used by B aldridge et al .(ref. 2-12) in con junc t ion wi th f r ames of h igh -a l t i t ude -a ircraf t pho tographs to ident i fy topographic featurestha t are not measurable in the Sky l ab pho tographs a l onebecause of inadeq uate stereographic p aral lax. This pro-cedure involved simul taneous viewing of the ai rcraf tpho tographs ( acqu i red at an earl ier date) and Sky l abpho tographs of the same area and at the same scale. Th eresultant stereoscopic effect provided the investigatorw i t h a m ea n s to define th e slope of land features and toevaluate th e temporal impact on the landscape.

The potential of using S190B photographs for thedetection of nonfuel surface mining (e.g. , clay, sand ,gravel , an d phosphate min ing) w as also assessed byHannah , We l by , and W eir (refs. 2-2, 2-13, and 2-20,respect ive ly) . Because clay mines range in surface areafrom 0.4 to 2 h m

2, they are d i f f i c u l t to detect in space-

acquired imagery . However , the larger sand and gravelmines , with the i r lobate geometry and associated waterbodies, provided a dist inc t ive pat tern and w ere easilydetected and ident i f ied. The very distinct signature cre-ated b y p h o s p h a t e m i n i n g in central Flor ida (h igh ly

ref lect ive surface produced by bare sandpi les) indicatesthat this type of excavat ing and associated reclamationact ivi t ies can easi ly be ident i f ied and mapped by usingspace photograp hs ( ref . 2-2) .




[a

S c a l e , k m

,

FIGURE 2-18.—An S190B photograph show ing st rip mines in the M adiso nvi l le , Ke ntuc ky , area (SL4-90-032). (a) This synopt ic view a l l o wsi den t i f i c a t i o n of surface coal s t r ip-mining opera t ions in an a g r i cu l t u ra l reg i o n, (b) An en l a rg em en t of a smal l segment of figure 2-18(a). Th e

features associated with an act ive st r ip-mining opera t ion are ident i f ied . This scene shows the amount of detail that can be seen in an enlargedportion of an S190B photograph.

48 S K Y L A B E R E P I N V E S TI G A T IO N S S U M M A R Y



Ib )

1. Ramp roads

2 . Active pit and minor roads3 . Graded

Exp lanat ion

4. Planted

5 . R eclaimed6 . Shadows from spoil hi l l s

F I G U R E 2-18 .—Co n c l u ded .

Scale, km

IV




T AB L E 2-XVI.—Summary of Qualitative Feasibility of Using Skylab SI 90B Data

to Identify Surface Coal-Mining/Reclamation Features

Feature

Lack of vegetat ion

High wal ls

Slope ( recognized but not m e a s u r a b l e )

Coal seam

Spoi l b a n k s

Access roadsE q u i p m e n t

Skylab Principal Investigator

Results

Act i ve s t r ip m i n e

b )

f b )

(b): h

(a )

(e )

Baldridge (ref. 2-12)

Minimum area discernible

using color-infrared film, hm -

land

" -

-

:

-

(c

c )

( d )

Brooks

(ref. 2-19)

results

(a)(a)

(c)(Q

h i(a)(g)

Weir

(ref. 2-20)

results

(a)(a)(e)(e )(b )

(a )(I)

Orp h ane d s t r i p m i ne l and

No vege tat ion or sparse vege tat ion

High wal l s

Spoil b a n k s

I m p o u n d m e n t sI m p o u n d m e n t qual i ty

Access roads

(a)(b)(b)(a)(e)(b )

0.5 to 1

(c )(c )

0.5 to 1

(d )(c)

(a)(b)(b)( a )

(b )

(b)

(b)(b)(b)

(a)^

(b )

Ongoing r e c l a m a t i o n and r e c la i m e d s t r ip m i ne a re as

E q u i p m e n t

Smooth s lopesVegetation: 0- to 40-percent cover

Veg e ta t io n : 40- to 80-percent coverVeg e ta t io n : 80- to 100-percent cover

I m p o u n d m e n t sI m p o u n d m e n t qual i ty

Access roads

(e)(b)(b)(b )(b)

. , ,(e)(b)

(d )

(d )1 to 5

1 to 5

1 to 5

0.5 to 1(d )(c)

(g)M l

(b)

(b)

b)

(a)(b)(b)

e i

M i

(b)

(b)

(b )

(a )(g)

f b )

"Us ual l y d e t e r m i n e d wi th ease from SI90B

bDetermined of t en enough to make dat a us eful

c N o i nfor mat ion p r es ent ed .

^Not app l i cabl e

Information des i red bu t unobta inabl e f r om S190B.fR a r e l y ob ta ined from S190B

^ I n f o r m a t i o n desired bu t no t subjected to i nves t i ga t i on wi t h S190B

5 0 S K Y L A B E R E P I N V E ST I G A TI O N S S U M M A R Y



The overal l conclusion is that S190B-type photo-g r ap h s can be used fo r detection and m a p p i n g of thesmall surface mines and th a t th i s kn o wled g e can beused by Federal and State agencies and local groups th at

are concerned with resources , reclamation , and l an d useman ag emen t . Al th o u g h n o n e o f th e S ky lab in v es t ig a -tors spec if ical ly evaluated the S190B pho togr aph s foro th er typ es o f su r f ace min in g ac t iv i t ies ( c o p p e r ,

u r a n i u m , and l i m e s t o n e ) , it is o bv io u s th a t S ky lab - t yp e

p h o to g rap h s co u ld be usefu l f o r ma p p i n g an d m o n i to r -ing d is turbed areas associated w i t h su ch min in g o p era -tions (fig. 2-19).

W e l b y and Lammi (ref . 2-13) indicated that S190Acolor-infrared film can be used effectively as an aid indetecting sediment d ischarge f rom active or aban d o n edq u a r r y o p e r a t i o n s , p r o v i d i n g t h e r e c e i v i n g - s t r e a mwate r s are a p p r o x i m a t e l y 60 m w i d e . N o r m a l l y , w a t e rwi th h ig h sed imen t co n ten t w i l l have a m o r e h ig h l y

ref lect ive surface than w i l l other stream water.

Wetland mapping an d ecology.—The fragile ecological

zone that forms th e bo u n d ary be tween lan d a nd watermass , t e rmed the "coasta l wet lan d s , " has become an in-creasingly critical area requir ing th e es tab l i sh men t ofeffective management practices . Laws regulat ing th etyp es of act ivi ty in wetlands have been enacted by most

of th e affected S tates . Anderson et al. and K l e m a s et al.(refs. 2-21 and 2-9 , respectively) examined th e p o t e n t i a lof using spacecraf t-acquired data to mo n i to r and mapthese areas in a p rac t ica l and in exp en s iv e man n er .

A nde r son ' s f ind ings (ref . 2-21), in p a r t i cu la r , ind i -

cate th a t o rb i ta l p h o to g rap h s ( p r i m a r i l y th e SI90A col-or - inf rared and S190B color f i lms) are the best data basebe in g used fo r rap id , rela t ively lo w cost wet lan d map -

p in g and m o n i t o r i n g on a regional basis. Figures 2-20(a)and 2-20(b) are two SI90A color - inf rared pr in ts ac -qu i r ed over Anderson's test site at the mo u th of theN a n t i c o k e R i v e r in Do rch es te r Co u n ty , Mary lan d ;

figure 2-20(c) is the co mp i led wet lan d s map . In map -

p i n g th e marsh categories, th e tonal contrast of the col-

or - inf rared film and the texture patterns were found tobe the m o s t imp o r tan t r eco g n i t io n elements in the p h o -to in te rp r e ta t io n an a lys i s . At tem p ts w i th the use of

S c a l e , k m

F I G U RE 2-19 .—An S190B color photograph showing th e large open-p it copper mine in Bingham C a n y o n , U t a h . T h e act ive ly m i ne d area

and the mine ta i l ings should be noted (SL3-83-300).

o th er en h an cemen t tech n iqu es (co lo r - ad d i t iv e v iew in gand density s l icing) were unsuccessfu l in producing d is -t inc t ive s ignatures in the areas of interest and effec-

t ively separating th e various categories and i n d iv id u a l

species. The S190A color film provided sl igh t ly better

r eso lu t io n , bu t tonal contrast (greens a nd b r o w n s ) w asnot as d is t in g u ish ab le as the shades of red and blue inth e co lo r - in f r a r ed film. The S 1 9 0A b lack-an d -wh i te in -frared film also provided som e in f o rmat io n in th e




5 2 S K Y L A B E R E P I N V E S TI G A TI O N S S U M M A R Y



(c )

I [ U p l a n d

IIW a t e r

P ] N e a r s a l i n e

| | T y p e I, fresh estuarine river

I, j T yp e m, fresh estuarine bay

^]Type II , b r a c k i s h estuarine r i v e r

feS^Type IV, b r a c k i s h estuarine bay0 5

S c a l e , k m

F I G U R E 2-20.—S190A co l o r - i n f r a r e d photographs an d a c o mpi l ed w e t l a n d s map for the marshes o f Dorchester C o u n t y , M a r y l a n d . This t yp e of

temporal pho to g r aph ic c o v e r ag e was usefu l for the delineation o f w e t l a n d boundaries, (a ) S190A co l o r - i n f r a r e d pho to g r aph ob t a i ne d in June

1973 (SL2-15-174). (b) S190A c o lo r - in f r a r ed p h o t ogr a p h ob t a i ne d in September 1973 (SL3-39-123). (c) Com p i l e d wetlands m a p .

marsh areas . The final produc t prepa red f rom bothscenes ( J une and September) indica ted th e va lue oft empora l data in a c c u r a t e l y de t e r m i n i ng b ounda r yplacemen t dur ing the map ping of marsh ca tegor ies andin identifying ind ivid ual species . The J une data wereused to dis t ingu ish the m arsh areas f rom the uplandsand the b rack i sh r iv e r marsh f rom the f resher wa te r ;they a lso enabled the del ineat ion of certa in ind iv idual

species by th eir char acte ris t ic color . The Sep temberphotographs were super ior fo r de l inea t ing th e u p p e rmarsh boundary ( i .e . , wooded swamps are drier in thef a l l and provide bet ter contras t) a nd m a r s h / w a t e r i n t e r-faces because of reduced vegetat ion cover.

Anderson points out th at , from analy s is of theS190A data , i t was poss ible to deve lop a we t l a ndclassification sys tem tha t inc luded f reshwa te r t ida l wet-

l ands and also to detect in d iv id u a l species when theyoccurred in rela t ively large stands. Several d i f fe ren t

species (not shown in fig. 2-20) were identified andmap ped , and several subcategories of marshes were a lsoidentif ied .

Th e S190B color photographs of Great Egg H a r b o r ,New Je rsey , were examined by Anderson , who indi -cated that these photographs were s imi l a r to h igh-al t i tude aerial data with respect to the amount andsharp ness of deta i l . W ithin this area , the upp er ma rshb o u n d a r y , t h e m a r s h / w a t e r i n t e r f a c e , a n d t h eperim eters of marsh areas were easy to del ineate wi thth e S190B photographs , and less sub j ec t ive j udgmentwas involved than w i t h the S190A photographs . Figure2 - 2 1 (b) is a map of the same area compiled fromanalysis of figure 2-21(a), an S190B photograph of the




FI G UR E 2-21.—S190B color photograph (fig. 2-21 ( a l ) of G rea t Egg Harbor , N ew Je r s ey , and a coastal wetland map ( f ig . 2 - 2 1 ( b ) ) compiled

from an analys is of the Skylab photograph. Th e increased spat ial resolu t ion of the S190B color f i lm enhanced boundary del ineat ion and p l a ce -m e n t an d also enabled ident if ica t ion of more botanica l ca tegories than w as possible w i t h th e S190A photograph, (a ) S190B color photograph

(SL3-86-303). (b ) Coastal w e t l a n d m a p .

New Jersey s i te with an approximate scale of 1:110 000.The land/w ater interface , dra inage pat terns , di tch ing ac-t iv i ty , and vege ta t iona l d i s t r ibut ion are well di sp layedon the photograph. As a resul t of the excel lent tonalcontras t on the S190B color photog raph s , i t was poss iblet o d i s t i n g u i s h t h e b o u n d a r y b e t w e e n s a l i n e a n dbrack i sh wetland and to del ineate the t rans i t ion zone(be tween wet l and and upland) wi th the b rack i sh we t -l and . The transi t ion zone w as easier to del ineate on theS kylab photograph than on l ow-a l t i tude -a i rc ra f t pho to-

graphs . As a resul t of these s tudies , Anderson (ref .2-21) modified the class if icat ion sys tem to separatesal ine wetlands that have been affected by h u m a n ac -tivity from unaffected sa l ine wet lands (a na tu ra l ly oc -cu r r in g state).

Migratory waterfowl hab itat evaluation.—The ma jorobjective of the migra tory w a te r fow l hab i ta t inves t iga-t ion (conducted in eas te rn Nor th Dakota ) was to m o n i -to r changes in the breeding hab i t a t of migra tory wa te r -fowl between M ay ( the peak nes t ing season fo r several

5 4 S K Y L A B E R E P I N V ES T IG A T IO N S S U M M A R Y



B r a ck ish wet land

Upland

Transi t ion zone

Sal ine wetland, d i tched

W a t er

Developed barr ier is land

W et land impoundmenta l ine wet land

not di tched

F I G U R E 2 - 2 1 . — C o n c l u d e d .

species of ducks) and July or early August (when mostduck broods h ave hatch ed) . Proposed indic ators ofhab i t a t quali ty were surfac e wa ter, gene ral degree of ter-rain wetness , plan t ph enolo gy, and land use pat te rns .Pr imary emph asis was placed on the observat ion of sur-face-water features (ponds and lakes) to obtain s ta t is t i -ca l data on the num b e r of surface-water features andth e i r areal extent , dis t r ibut ion, and frequen cy. Such in -format ion is used in models fo r p r e d i c t ing a nn ua lwater f o wl produc t ion . The EREP da ta were not ob-tained over th e test site during the May 1973 breeding

period but were obtained on June 12,1973, between theM ay and Ju ly dates des ired. Resul ts of the ana lys i s ofth e EREP da ta were the re fore compared to those ob -tained by Landsa t on M ay 1 4 and J u l y 7 , 1973.

In t h i s Skylab s tudy , th e SI92 scanner sys tem datawere ana lyzed by digital com pute r a na lys i s techniques .The use of computer data-processing techniques is par-t icular ly wel l sui ted to th is t y p e of analys is because ofth e wide expanse of p r i m e water f o wl -br eed in g area in -volved and because of the need to q u ick ly ass imila teand col la te inform at ion on hab i t a t condi t ions .




•

- A r r o w w o o dL a k e

- M u dL a k e

u

"

B a r n e sLake-.

,'Jim.-•' L a k e \

. ../ rt *

Jamestown

R e s e r v o i r— —

S c a l e , k m

F I G U R E 2-22.—A segment of a computer-genera ted surface-water m ap produced by processing band 11 (1.55 to 1.75 ^m ) data from th e Sky labS192 mult ispectral s c anner observat ion of an area nor th o f J a m es t o w n , N o r t h Dakota . The open surface water is shown i n b l a ck .

To del ineate surface-water boundar ies , a level-sl icingt e c h n i q u e w as used to ana l yze th e data from a singlenear - in f ra red band . This reasonably re l iable and fairly

s impl e m e thod w as effect ive because of the very high

absorpt ion and therefore lo w reflectance of water inthese near- infrared wavelengths. Pre l iminary study ofth e data indicated that any one of the five wave l eng thbands from 0.78 to 1.75 pm woul d be po ten t i a l l y usefulfo r disc r imin at ing open surface water by using such at h re sho l d ing t e chn ique . Th u s , th e EREP data offeredan o p p o r t u n i t y to appra i se th e relative usefulness andre l iabi l i ty of several di ffere nt near- infrared wavelengthbands . Th e results of th is evaluat ion indicated that baresoil was the te rrain feature most l ikely to be mistakenfo r open surface water . Al though th e problem was notsevere , there d id seem to be a tendency for water andbare soil to have some overlap in level of spect ral

response. Th e pre l im inary work wi th th e S192 data ind i-cated that this over lap decreased with increasingwavelengths. T hus , th e 1.55- to 1.15-n.m wavelength

b a n d was the most useful single band fo r effective waterdiscr iminat ion. Using th e thresholding technique andth e 1.55- to 1.75-j tm wavelength band, a compute r -generated themat ic map ident ify ing open surface water

was obtained for a 3618-km2

area (fig. 2-22).In a comparison of the Sky l ab results with those

from a naly sis of Landsat d ata collected in May and Ju ly1973, Gilmer an d W ork ( ref . 2-15) found that , on a syn-optic basis, the two sensor systems appeared to provideconsistent answers in that both data sets indicated adecline in area and n u m b e r of surface-water features. Am or e detai led comparison of the size of 21 ind iv iduallakes that appeared on all data sets indicated that th eSkylab mul t i spect ral scanner was not capable of achiev-ing as consistent a measure of area as the Landsat scan-ner. The invest igators at t r ibuted this resul t to the coni -ca l scan con figurat ion used by the Sky lab S192 scanner .G i l mer and W ork bel ieved that both th e scanning for-mat and the associated techniques fo r data processingappeared to have the net effect of slightly but

5 6 S K Y L A B E R E P IN V E S TI GA T IO N S S U M M A R Y



sys temat ica l ly a l ter ing th e m e a s u r e m e n t s and t hegeometric f idel i ty of smal l ponds .

Another phase of this s tudy involved a more l imitedtes t ing of a different technique for improving the ap-parent spat ia l resolut ion of the Skylab S192 data . Thistechnique was described as a proport ion es t imationtechnique and involved the use of a com puta t ion a la lgor i thm fo r es t ima t ing th e f rac t ions of pure m a te r i a lspresent w ith in the resolut ion cel l of a mu l t ispectra lscanner. The deta i ls of this technique are described insection 6. Resul ts of this analys is indicated that th em inim um discern ible s ize of a water body w as four-t e n th s of the minimum size that could be detected byu s i n g t h e s i n g l e - b a n d t h r e s h o l d i n g a l g o r i t h m .Therefore, this technique seemed to offer considerablepromise fo r m a pp i ng and tabula t ing much sma l l e rwater bodies than could be achieved by using th ethresholding technique. Gilmer and W ork a lso foun dthat , by us ing the proport ion es t imation technique,some lakes that had been only part ly defined with

Landsat data could be fully defined with the SI92 data .Such lakes were sh al low and a lka l ine, with a high levelof suspended solids and/or precipi ta ted a lkal i sediment .The imp roved cap abi l i ty for del ineat ing such lakes wasa t t r i bu t ed to the middle-infrared spectra l b a nds associ-ated with th e S192 data that extended to 2.35 /u.m,whereas th e Landsat scanner system had only tw o near-i n f r a r e d w a v e l e n g t h b a n d s w i t h a m a x i m u mwavelength of 1.1 m. The 1.55- to 1.75-/u.m wavelengthband is par t icularly effective in the d el ineat ion of waterand hygric-scene features in general.

T A B L E 2 - X V I L —Non-Principa l - Inves t iga tor User Agencies

Skylab Geographic

Princ ipal area

Investigator

User agencies

P. E. Baldr idge O h i o D e p a r t m e n t o f Eco n o m i cs

( com m uni t y d e v e l o p m e n t ) .D e p a r t m e n t o f N a t u r a l

Resources (city, c o u n t y , a ndregional agencies)

R. L. Bro o k s K e n t u c k y State coal s t r i p m i n e i n spec t o rs ,

ot h e r State o f f i c i a l s

J . W . H a n n a h F l o r i d a Ci t y , county ( regional p lan n in g )

E. E. Hardy New York Ci t y , county , regional (Sta te

p l a nn i ng an d en v i r o n men ta l

research)

R.M . Hoffer Co l o ra do

U.S. Forest Service , N a t i ona lPark Serv i ce

I . J. Sat t inger Michigan Bureau of O u t do o r Recrea t i o n ,

O a k l a n d C o u n t y P lan n in g

Co m m i ss i o n , Mic h ig an

D e p a r t m e n t of N a t u r a l

Resources

C. W. We lby N o r t h Carol ina D e p a r t m e n t of N a t u r a l

Resources (economic resourcep lan n in g , e va l ua t i on )

User Evaluat ions

In addi t ion to y ie ld ing th e specific benefits derivedby the individual invest igat ions , the Skylab Programpromoted a much broader concept of technologytransfer to a diverse user audience. Through the effortsof the Princ ipal Invest igators and the ir direct contactwi th differen t user-agency groups , inclu ding local, coun-ty, regional, State, and Federal user communit ies , th euse and evaluat ion of the Skylab ER EP d a ta havereceived a significant amount of exposure.

From th e initial select ion o f the S kylab Principal In-vestigators and ex tending through th e data analys is

period, considerable emphasis was directed toward ac-tual or potent ia l user involvement with the data prod-ucts generated from this uniq ue remote-sen sing system.

In some cases, th e Princip al Invest igators themselveswere represent ing various user agencies. In many othe rinstances, th e Princ ipal Invest igators contacted v ariousagencies h aving re spon sibi l i ty with in their test -si te areaand worked wi th th e personnel of those agencies to pro-duce specific Skylab products for use and ev aluat ion bythose agencies. Table 2-XVII is ind ica t ive of the num -ber and variety of non-Principal -Invest igator user agen-cies that were involved indirect ly in Skylab land use in-vestigations. Th e fol lowing paragraphs ci te some exam-ples of the specific types of activities that were in-volved.

The major user of remote-sensing data for surface

mining appl icat ions in Ohio ( the Ohio Department ofNatura l Resources) indicated that the potent ia l useful -ness of EREP-type da ta for cur rent mining and




rec lamat ion act ivi t ies has been sat isfactor i ly demon-strated and that both sate l l i te and ai rcra f t data are nowbeing used in State of Ohio min ing an d rec lamat ion pro-grams . Another Skylab invest igator worked di rect lyw i t h State of Kentucky coa l -min ing officials w h o indi -cated that i f Skylab qual i ty imagery w ere avai lable on a

regular ly recurr in g basis , the overal l s t r ip -m inin g pro-gram could be upgraded t h rough it s use.

The usefulness of space pho tographs w as cited by themembers of the O h i o D e p a r t m e n t of E c o n o m i c andCommuni ty Deve l opment i n t he i r s t udy on u rbangrowth enc roachmen t on agr icu l tu ra l l and . Par t i c i p a t ingregional planners concluded that th e capabi l i ty tomeasure u rban g rowth and i ts i m p a c t on the regioncould be of i m m e d i a t e use to p l anne rs in eva l ua t ing th eeffectiveness of both regional and local policies.

The SI92 d igi tal data and SI90 imagery were used toderive computer-generated c lassi f icat ion maps and pho-tointerpre ted land use maps, respect ive ly , for different

levels of planning agencies in Florida. A ma jor i ty of theuser group surveyed expressed a st rong preference forth e largest scale m ap possible, regardless of the datasource used.

In surveying the user evaluat ion of EREP data, atwo-phase app roach w as in i t i a ted— an in t roduc to ryphase dur ing which th e potential user w as famil iar izedwith the concept of mul t i spect ral analysis and wi th theuse of E R E P data products to del ineate cer tain landuses a n d n a t u r a l c h a r a c t e r i s t i c s a n d a n i n - d e p t hfo l lowup in terview st ructured around a de tailed ques-t ionnaire . These surveys showed dist inct di fferences inresponse between different categories of users. Theregional planners were more interested in long-term in-

t e r re l a t i onsh ips and were enthusiast ic about th e E R E Pdata because th e synopt ic view obtainable f rom spaceoffers an unparal le led method for accurate ly showingvarious land use pat t e rns on a regional scale. Localagencies, involved in day-to-day decisions, general ly in-dicated a requiremen t for more d e tai led informat io nthan could b e obtained from th e E R E P p r o d u c t s . Inmost instances, the i r needs could best be met by usingdata col lec ted f rom ai rcraf t . The impor t an t po in t to bem a d e is that cer tain user groups do have a need fo r suchsynopt ic data, whereas other user groups require moredetailed data over smaller areas.

Summary

A s i g n i f i c a n t n u m b e r o f S k y l a b i n v e s t i g a t o r sdeveloped and demons t ra t ed th e usefulness of thep h o to g rap h ic sensor systems and the i r appl icat ion toresource inventor ies and ana l ys i s fo r l arge geograph ical

areas, as wel l as to regional and local uses. Both conven-t ional pho to in t e rp re t a t i on and computer-assisted pro-cedures were effect ive in the ana l ys i s of E R E P d a t a .Many spec i a l app l i ca t ions ( i n c l u d in g su r face min ingoperat ions, we t land area map pin g, change detect ion ofu rban pa t t e rns , and general land use m a p p i n g ) i n v o lv -in g t he use o f mu l t i band and color- infrared p h o t o g r a p h swere successful ly dem onstrated. W ith fe w except ions,repeti t ive data of the t ype ob t a ined by Sky l ab (p r imar i l ywith the S190B) can meet most i nve n to ry ing and m ap-p in g r equ i rement s . Par t i c i pa t ing p l anne rs conc l udedthat the cap abi l i ty to moni tor u rban growth an d i t s im-pac t on the region has imm ediate value to land use plan-ner s in evalu at ing the effect iveness of both regional andlocal policies related to growth .

The Skylab S190B p hoto grap hs enlarged to scales of1:63 360 and 1:24 000 pro vid ed sig nifica nt detail foreasy and eff ic ient map ping . The S190B ph o tographswere c i ted by m ost invest igators as be ing super ior to theS190A photographs because of the grea t e r amount ofdetai led informat ion that could be der ived from thesepho tograph s. Studies inv olvin g urban areas were pa r t ic -ular ly amenab l e to the use of the S190B color filmbecause th is f i lm provided adequate spat ial resolut ionand therefore th e most detai led informat ion. Also,many invest igators s tated that the color- infrared pho to -g raphs we re i nva l uab l e fo r man y app l i ca t ions r equ i r ing

identif icat ion of vegetative cover. Therefore, an op-t imum sys t em fo r many inves t iga t ions woul d havecombined the high-resolut ion color f i lm and t he h igh -reso lu tion color-infrared film (SO-131) into a dualS190B camera system. A specif ic recommendat ion wast h a t f u t u r e o r b i t i n g s p a c e s t a ti o n s i n c l u d e amult ispect ral camera array composed of four S190B-type cameras. This design wou ld incorporate the addedf lexibil i ty that i s essent ial to expand and enhance thetype and qual i ty of i n fo rmat ion fo r general land useprograms .

A group of Sky la b invest igators provided much in -

5 8 S K Y L A B E R E P IN V E S T IG A T IO N S S U M M A R Y



sight in to the use of compute r -proces s ing t echniques fo ran a lyz in g SI92 m ul t i spec t ra l s canner da ta fo r l and useappl icat ions. Overal l accuracies of 75 to 90 pe r c e n t fo rclassification of Leve l II l and use maps were achievedby using such analys is techniques . Areal es t imatesbased on computer-a ided analys is were h igh ly corre-

lated w i t h t hose ob ta ined through s t anda rd photo in-te rpre tat ion t echniques appl i ed to ai rc raf t pho t og r a phs .

The increased spectra l range, from the vis ib le

t h rough th e t he rma l - inf ra red wave length , of fe red bythe SI92 scanner sys tem provided invest igato rs withthe f i rs t opportuni ty to analyze this wide spectrum ofdata from satel l i te a l t i tudes . The consensus of the in-ves t igators was that a t leas t one wavelength band fromeach of the four major port ions of the electromagnet icspectru m (vis ible , near infrared , midd le infrared, andtherm al infrared ) was necessary to achieve op t im alcomputer class if icat ion of l and use categories. The near-inf rared port io n of the spec trum was found to be part ic-

ular ly i m por t a n t fo r accura te d i s c r imina t ion amongvarious vegetative cover types. In other studies, a com-

b ina t ion of six w aveleng th bands was ci ted as being op-t imal fo r land use m a pp i ng w i t h the use of c om pu t e r -aided analysis techniques.

In general, the Sky lab SI 92 land use in vestiga torsconcluded that th e impro ved spectra l resolut ion and theincreased spectral range available in the SI92 scannersys tems (a s compared to the Landsat-1 sys tem) enabledsignificant i m pr ove m e n t in class if icat ion performancefo r land use m a p p i n g . A few inves t igators ind icated thatth e improved spectra l resolut ion obtained in the Skylab

scanner data was m or e impor tant for mapping man ycover-type features than was the spat ia l resolut ion ob-ta ined through use of the S190 photographic sensorsystems.

In one invest igat ion, camera data from Skylab andLandsat were geometrically corrected to a topographicm ap (scale, 1:24 000) of the Durango, Colorado, areafo r th e purpose of quant i t a t ive and qua l i t a t ive com-

parisons and analyses. The use of various analysis tech-niques w ith this data set provided some insight into thevalue of working with topographic data in conjunct ionwi th mult ispectra l scanner d ata for land use and major-cover-type mapping in a topographical ly and vegeta-t ionally complex mountainous region.

In nearly every s tudy in which S192 data were usedin conjunc t ion wi th compute r -a ided a na lys i s tech-niques , th e inves t igators concluded that t r a d i t iona l

defini t ions of land use categories often w i l l no t p r oduc espect ral ly separable in form atio nal classes of data out-

put . To ob ta in max imu m benef it f rom mul t i spe c t ra l

scanner data, it will be necessary, in many cases, to es-tabl ish land use category defini t ions that are based onspect ral ly d i s c r i m i na b l e classes of cover type.

T h e S kylab E R E P e x pe r i m e n t de m ons tr a te d t heval ue of photographic and mul t ispectra l scanner dataobtained from satel l i te a l t i tu des fo r many l and use m a p-p in g act ivi t ies .

CARTOGRAPHY

The process of produc ing and m a inta in ing qual i ty

m a ps and other precis ion cartographic products is com-

plex, t ime consuming, and cost ly. Despi te the obviousneed fo r more and bet ter maps and the use of h i gh l ysophis t icated equipment and techniques in their pro-

du ction , it is estimated tha t on ly about 30 percen t of theEarth ' s landmass is now adequately mapped. Further-more , in rap idly developing locales , maps are often ob-solete by the t ime they are constructed and publ i shed .

Before the advent of pract ical aeria l photography,maps were made in the field by teams of cartographersw h o pain s takin gly measured their w ay over th e land-scape. During th e 1920's an d 1930's, s ignificant ad-vances were made in the developm ent of a i rcraft ,photography , and optics. These advances m a de photo-

grammet ry—the art and science of deriving rel iablemeasurements from photographs—increas ingly impor-tant in the produc t ion of m a ps . Through the use ofspecia l ized cameras , cus tomized photographic flight

equipment , and complex monoscopic and stereoscopicplot t ing equipment , a major port ion of the m a p m a k i n gprocess was shifted from the field to the office. This useof aeria l photographs made it possible to accelerate m approduc t ion and to produce maps having increasedgeometric accuracy and detail . In recent years, car-

t og r a phe r s h a v e t u r ne d to large-scale , high-speedelectronic com puters and improved mathematical tech-niques to increase th e speed and accuracy of map pro-




duc t ion . Today , pho togrammet r i s t s and car tographe r scons ide r pho tographs and digi ta l image ry f rom o rb i t in g

spacecraf t as the next major step in the prepara t ion andrevision of many types of m a p s .

The Skylab S190A and S190B cam era systems pro-duced s ate l l i te pho tographs of re lat ive ly high m etr ic

and re so l u tion qua l i ti e s and p rov ided car tographe r sw i t h a viable means of test ing and eval ua t ing th e car-

tograph i c po ten t i a l o f space pho tograph s . In t he Un i t edS ta te s , t he p r im ary p rob l em in map p ing i s the r ev i s ionand upd at ing o f ex i s t i ng maps . In many o the r r eg ions o fth e wor l d , par t i cu l a r l y in deve l op ing coun t r ie s and/or

remote areas, th e product ion of new maps is of para-mo unt co ncern. M ost of the invest igat ions using Sky labS190A and S190B pho tographs fo r original m a p p i n gwere conducted b y agencies or organizat ions outside th eUni t ed States. The p u r p o s e of th is subsect ion is to sum-marize th e results of the Sky l ab ER EP ca r tograph i c in -vest igat ions and to indicate possib le improvements in

car tograph i c i ns t rumenta t ion and t e chn iques fo r fu tu respace missions.

Sensor Technology

In consider ing th e results of expe r imen t s pe r fo rmedby the car tograph ic invest igators , i t i s imp orta nt to notetha t ne i t he r th e S190B terrain camera nor the camerasc o m p r i s i n g t h e S 1 90A m u l t i s p e c t r a l a r r a y w e r edesigned fo r car tographic appl icat ions. However , th eS190A and the S190B d id represent s ignif icant metr icand resolut ion advances in camera systems for Ear th

pho tograph i c obse rva t ions f rom space , and several car-tographers at tempted to exp l o i t fully some of the photo-g raphs .

Applications

Aside from charts, w h i c h a re spec i a l -purpose mapsused for ai r or water navigat ion, the most widely usedcar tographic products are p l an ime t r i c and t opograph i cm a p s and control led photomosaics. Planimetr ic mapsreveal only the hor izontal locat ions of surface features,whereas t opograph i c maps show add i t i ona l l y th e vert i -cal posi t ions of features by displaying relief in some

measurable form. On maps, re l ief i s depic ted by a con-tour l ine , wh ich is an imag inary l ine on the ground thatconnects a ll points that are a t the s a m e elevat ion above

a specific datum surface (u sual ly mean se a level). Apho tomosai c i s a con t inuous ph o tograp h i c r ep re sen ta -tion of a por t ion of the Earth ' s surface , prepared by as-s e m b l i n g i nd iv idua l pho tograp hs t ha t have been ren-dered "ti l t free" by a process termed rect i f ica t ion.

Planimetr ic and t opograph i c maps and pho tomosai c s

are produced in a wide range of scales; however , mostof these i tems range from 1:24 000 (1 cm equals 0.24km) to 1:500 000 (1 cm equals 5 k m ) . In the U n i t e d

States, scales of the s t andard na t iona l car tograph i cproducts are 1:24 000, 1:62 500, an d 1:250 000. Inmetr ic -system-oriented par ts of the wor l d , th e morec o m m o n l y used scales are 1:25 000, 1:50 000,1:100 000, 1:25 0 000, an d 1:500 000. M aps h av ingscales between 1:75 000 and 1:600 000 are general lyclassed as med ium-sca l e maps , whe reas maps hav ingscales greater than 1:75 000 are considered large-scalemap s. In most usages or app l icat ions, one general lyseeks th e smallest scale m ap capab l e of dep i c t i ng th e

degree of de tai l required to supp ort the par t icu lar ap-plicat ion .

Photogrammet r i c map p ing requ i res t ha t th e pos i t i onand the orientat ion of the camera taking th e pho tographbe de te rmined at the i n s t an t of exposure . This in fo rma -

t ion is general ly obtained by means of a n e t w o r k ofp h o t o i d e n t i f i a b l e " c o n t r o l points," fo r w h i c h t h ehor izontal and/or ver t ical locat ions have been estab-l i shed by ground survey. After a basic ne twork ofground control has been establ ished, photogrammetr ict r iangulat ion m et h o d s are usually used to extend th ebasic control ne twork. Fo r each photograph being usedin pho togrammet r i c mapp ing o r i n t he p repara t ion o f

control led photomosaics, six to nine control points ,well dist r ibuted over th e fo rmat , are required. The es-t ab l i shment of basic groun d control and densif icat ion ofth e con t ro l ne twork are usual ly th e most costly andt ime -consuming por t i on of the overal l photogram-me t r i c mapp ing process, especially in remote regions.

If camera parameters such as lens focal l ength andfilm f o rmat rema in constant , th e higher the al t i tud efrom w hich a photograph is taken, the greater theground area that appears on the p h o t o g r a p h . An in-crease in al t i tude reduces the number of photographsrequired to cover a g iven area and , mos t impor t an t l y ,increases th e distance between th e required surveyedground control points and thus reduces th e overal l

number o f mandato ry con t ro l po in t s . The fo rmat s o fth e S190A an d S190B ar e signif icant ly sma l ler than con-vent ional ma pp in g cameras (5 .7 cm and 11.4 cm ,




r esp ec t iv e ly , com pared to 22.8 cm ), and the 45.72-cmfocal l ength of the S190B is three t imes longer than th el ens used in many conven t iona l mapp ing cameras .Neve r the l e ss , as s h o w n in figure 2-23, th e increase inarea of ground coverage by the S190A and S190Bsys t ems i s s t r i k ing by compar i son to conven t iona l

ai rc raf t pho tographs .Most of the Sky la b E R E P i n v e s t i g a ti v eefforts in car-

to g rap h y were di rected toward (1) the revision and up-d a t in g of exist ing maps, (2) the establ ishment of photo-grammetr ic ground control , and (3) the const ruct ion ofnew p l an im e t r i c and topograp h i c maps and pho to -mosaics. In almost al l invest iga t ions, the emphasis wasdirected toward de termining the largest scale m a p p i n gtask or p r o d u c t t h a t th e S190A and S190B Sky la b pho to -g raphs we re capab l e o f suppor t ing .

M ap Revision an d Updat ing

Many innovat ions o f p rocedure s and t e chn iqueshave been developed over the past few years to imp rov eth e technology of revising and u p d a t i n g m a p s . The useof remote-sensing data f rom space plat forms for thispurp ose is not new; l imi ted exper im enta l revision p rod-ucts have been publ ish ed, based on Gemin i , Apo l l o , andLandsat data. Because Skylab pho tographs have im -proved spat ial and spectral resolutions, several m aprevision projects have been accompl i shed wi th the useof Sky la b data.

The m o s t extensive car tographic invest igat ion w asconducted by 17 Lat in Am erican car tograp hic agenciesth rough th e Inter -American Geodet ic Survey a t FortClayton in the Panama Canal Zone (Staples et al . , ref.2-22). A few representat ive examples are c i ted in thefol lowing paragraphs t o p rov ide some insight into theusefulness of and the economic benefits derived fromSky la b - q ua l i ty pho tographs .

A m a p revision project performed by Fernandez(ref. 2-22) for a l :50000-scale map of Santa C ruz,Bolivia , reveals th e economy of such revision pro-cedures. Stereopai rs of black -an d-w hi te S190A (0.6 to0. 7 / u .m) pho tograph s at a 1:1 500000 scale (enlarged2x from the origin al scale) were used in a stereop lotter

to compi le planimetr ic features. In th i s s tud y , th e imagequal i ty of the S190A photographs l imi ted the de tect ion

of changes to l inear cul tura l features ( roads) and the ex-tent of new major u rban g rowth pa t t e rns . Majo r

changes to the river channels were also compiled. Sig-

n i f i c an t l y , th e map revision w as accompl i shed w i t h i n a

24-hour per iod, wi th the use of exist ing photogram-metr ic e q u i p m e n t .

..- S190A

F IGURE 2 - 2 3 .—Re la t i ve areal coverage of the S190A, S190B, an dconvent ional ai rcraf t c amera s ys tems . Th e coverage is rough ly

square; therefore , th e side d i m e ns i ons g i ve n in ki lometers an ds tatute miles a re t yp i ca l .




E X P E R I M E N T D E A C T U A l /Z A C I O N

C H I I E 1 : 5 0 . 0 0 0 C O N C E P C / O N

1000 MO

1000 MO 0

EKO'O 1 50 000?ooo »oo 4000 MOO x

CONCEPOCJN, C H / L E

• UMMODf fCUUtM*MMW«fiOO«CA1/AO1 MfNOtM*- C M U H C X G

CIMHO O 1 CtAf ttrf.

•ilUtl 1*1*4(jC*»«

U M W V O

6 2 S K Y L A B E R E P INV E S T IGAT IONS S UM M ARY



Invest igators in several other Lat in American coun-tr ies upd ated exis t ing maps w ith S190A p hoto grap hs . InChile, Puccio (ref. 2-22) also used S190A (0.6 to0.7 ^m ) film to revise a l :50000-scale map ( f ig . 2-24).

The b lack -and -w hi te nega tives w ere ph otogra ph ica l ly

e n l a r g e d a n d r e c t i f i e d , t h e n r e g i s t e r e d t o t h e

topographic map. Pucc io indica ted tha t the t echn iquew a s i n e x p e n s i v e a n d t h a t s i g n i f i c a n t p l a n i m e t r i cfeatures such as urban densi ty pat terns and major newroads were extracted eas i ly.

Al though the S190A photographs were used in somemap revis ion act ivi t ies , m os t inves t igators preferred theS190B photograp hs because of the spat ia l resolut io n ofas m uc h as 15 m. The t y pe of scene contras t an d imagequali ty determines the extent to which S190B photo-graphs wil l enable i den t i f i ca t ion of ind iv idua l featurestha t can be compi l ed on to 1:50 000-scale map s. W ithoptical enlarg ing viewers and/or s tereoplot ters , ma ny

smal l nonl inea r surface features are discernible and can

be plot ted. However, th e capabi l i ty to def ine some re -quired features depends on the avai labi l i ty of ground-t ru th data . The S190B data are mainly color photo-graphs, but selected data passes were also taken withb l ack -and -whi t e and color - inf ra red f i lm. Th e S190Bfield of view of 11 881 km

2provides coverage of most

major metropol i tan areas with excel lent image qual i ty

for map scales of 1:250 000 and larger. A 9.5 x enlarge-m e n t will p r ov i de a scale of approximately 1:100000,an d enlargements of twice this scale to a 1:50 000 scalestil l provide sufficient image qual i ty to enable extrac-t ion of map da ta d i rec t ly f rom the pho tograph ic pr in t orfrom optical enlargers and/or s tereographic plot ters .

In Argent ina , Micro (ref . 2-22) prepared a par t i a l

revis ion of the Chascomus 1:250 000-scale p l a n i m e t r i cmap, us ing a b lack-and-w hi te pr in t f rom th e S190B col-

or film. He ind ica ted tha t th e data enabled th e m a pp i ngof new roads, rivers, lakes, small urban areas, andshorelines in this topographical ly subdued region a longth e Atlant ic coas t l ine of eastern Argent ina . Rai l roadscould be detected when they were paral le l to roads, andfarm buildings were vis ible when grouped. Other in-ves t igators (R omero , V enezuela (ref . 2-22); M orrel l ,Dominican Republ ic (ref . 2-22); S tewart , Canada (ref .

2-23); and M o t t et al . , England (ref . 2-24)) indicatedtha t th e S190B color film provided be t t e r in te rp re ta t ivedetails for updating 1:100000- and 1:50 000-scale prod-ucts . This deta i l is p r i m a r i l y due to the scene contrastsin th e p ar t icu la r frames used ra ther than the resolut ioncharacter ist ics of the color film.

E x c e l l e n t e x a m p l e s of l a rge -sca l e p l animet r i c m apr ev is io n are two 1:24 000-scale maps of Lubbock ,Texas, prepa red by the Defense M app ing Agency A ero-space C enter in St . Lo uis , M issouri . The S190B colorfilm fo r this task w as used in January 1974 when th evegetat ion w as do r m a n t , and th i s condi t ion a f forded ex -cel lent scene cont ra s t. The revi s ion m ap pin g was ac -compl i shed a t t he origina l 1:24 000 scale, and po lye sterma t te pos i t ives of two topographic m ap sheets wereused for the compi l a t ion base. A color photographicp r i n t ( 1 : 4 80 0 0 s c a l e ) a n d a c o l o r t r a n s p a r e n c y(1:200000 scale) were enlarged fro m second-gen era-t ion m ateria ls . The area of interes t on t his Skyla b fram e

covered a pp rox ima tely 3 perce nt of the tota l photo-graph i c area . Planim etric features were t ransferred tothe m ap base comp iled by use of a zoom transfe r scope.This ins t rument provides a capabi l i ty for v iewing thep h o t o g r a p h i c image and the map base s i m u l t a ne ous l yand thus enables th e operator to revise or add detai l inr e l a t i onsh ip to exis t ing map features. A po rt ion of anenlarged S190B photograph used for this revision iss hown in figure 2-25(a). Figures 2- 25(b) and 2-25(c) ,r e spec t ive l y , depic t only a sma l l pa r t of a 1:62 500-scalemap p roduc ed in 1957 and the changes and revis ionsder ived f rom the Skylab imagery . The photo in te rpre ta -t ion and compila t ion for this map revis ion effort of thetw o 1:24 000-scale Lubbock topographic sheets re -

quired 72 man- hours . In this case, rel iable interp reta t io nof ground features was accom plished on 40 X enlarge-m e nts (from the original scale) .

In other examples , both Stewart ( ref . 2-23) and Col-vocoresses (ref. 2-25) indicated that, because of errorsin photointerpreta t ion, revis ions to 1:50 000-scale mapsw i t h the use of S190B data were n ot co mp letely rel iable .They do, however, indicate that the S190B data can beused fo r part ia l map revis ion act ivi t ies if the qua l i ty ofth e origina l f i lm data is m a i n t a i ne d .

FI G UR E 2 - 24 . —Example of map revi sion using Sky lab S190A sta-

tion 5 photographs . Or ig inal m ap scale is 1:50 000. Changes to orig-

in a l m ap a re overpr in ted in p i n k .




• h eê - - ' ,p: • "HtWeSt End

=• • •

64 S K Y L A B E R E P I N V E S T I GA T I O N S S U M M A R Y



IS)

in

0 1

S c a l e , k m

F I G U R E 2-25.—Planimet r ic map revis ion of Lubboc k, Texas, and vic ini ty , (a) Enlargement of a port ion of an S190B color photograph

(SL4-94-111). (b ) P lan i m e t r i c m ap produced in 1957 by us i ng conve n t i ona l p h o t ogram m e t r i c m e t h od s . Scale of or i g i na l map i s 1:62 500.

(c ) Revis ion to p lan i m e t r i c m ap s h ow n in Figure 2-25(b) as derived f rom S190B photograph . Changes are s h ow n in color .

Ph o t o g r a m m et r i c E s t a b l i s hm e n tO f Ground Contro l

The es tab l i sh men t of ground contro l is one of them o s t exp en s iv e and t ime-co n su min g ta sks in car togra-

p h y . Thr e e qu an t i ta t iv e in v es t ig a t io n s b y th r ee separate

agencies in Canada, each using d i f f e ren t t ech n iqu es ofaerial t r iangulat ion ad justment (S tewar t , ref . 2-23), andan inve stigatio n in Engl and (M ott e t a l . , ref . 2-24) dem-

o n s t r a ted th a t h o r izo n ta l p h o to g rammetr ic co n t ro lcap ab le o f su p p o r t in g p lan im et r ic ma p p in g a t s ca les o f1:250 000 and smal le r can be d er iv ed f ro m S kylab

S 1 9 0A p h o to g rap h s . These s a m e investigators , and

Keller (ref. 2-26) of the Nat io n a l Ocean ic and At-mo sp h er ic A d m in is t r a t io n , f o u n d th a t p h o to g rap h sf rom th e S190B camera system, with it s longer focal

l en g th an d h ig h er r eso lu t io n , were cap ab le o f p ro v id in g

hor izontal contro l suff ic ien t to su s ta in th e co mp i la t io no f p lan im et r ic map s at scales of 1:50 000 and smal le r .

In h is tr ian gula t ion investiga tion , Kell er used a s tr ip

of 12 S190B photog raph s that covered a 648-km-long

swath f ro m Ch ar lo t te , No r th Caro l in a , to the R a p -p ah an n o ck Riv er in Virg in i a . W ith in th i s a rea were 29h igh ly identif ia ble ground contro l po in ts (road in tersec-

t ions , aeronautical a ids , and a i rp o r t r u n way en d s ) fo rwh ich p o s i t io n co u ld be d e te rmin ed f ro m s tan d a rd

1:24 000-scale US GS qu ad ran g le map s and N a t i o n a lOcean S u rv ey (NOS ) a i r p o r t su rv eys. A s tan d a rd N O Sc o m p u t a t i o n a l p r o g r a m t o p e r f o r m n u m e r o u s

s imu l tan eo u s ad ju s tmen ts of the 12-photograph s tr ip

was used in the analy sis . In these ad ju s tmen ts , d i f f e r en tsu bse t co mbin a t io n s of the g ro u n d co n t ro l and different

empi r i ca l weig h t in g s of the g ro u n d co n t ro l and p h o to -

gra ph ic measu remen ts were t r ied . Th e best resu l ts were




o bta in ed u s in g a 1 4-p o in t n e two rk o f g ro u n d co n t ro l .Th e r e m a i n i n g 1 5 p o i n t s of kn o wn lo ca t io n were u sedfor accuracy evaluation. This "best" solution yielded a

root-mean-sq uare (rms) hor iz ontal posit ion er ror of 15

m , w i t h 25 m be in g th e maximu m er ro r o bserv ed .

T h e abi l i ty to der ive ver t ical contro l or contour infor -

mation from aerial or orbita l photographs is largely afu n c t io n of a character is t ic of over lapping s tereoscopic

p a i r s o f p h o to g rap h s , t e rmed base /h e ig h t (B /H ) r a t io .The B/H rat io of such a pair of photographs is the ra t io

of the d is tan ce be tw een the camera exposure stations to

th e distance, or a l t i tu d e , of the cameras abo v e th eg ro u n d . I n co n v en t io n a l ae r ia l p h o to g rap h y (1 5 .25 -cm

focal l en g th , 23- by 23-cm format) with 60-percent for -

ward over lap , th is ra t io is approximately 0.6 . Because ofth e h ig h er a l t i tu d e o f th e EREP an d sma l le r f i lm f o r -mat (and longer focal length for the S190B), w ith 60-

percent forward over lap , the B/H rat io is 0.15 for theS190A and 0.10 for the S190B. Despite th e smal l B /H

ra t io , Mo tt e t a l . (ref . 2-24) perform ed a ver t ical ad just-ment of a s tr ip of seven S190B photographs taken overth e rugged te r ra in of N e p a l and achieved an rms h e ig h t

er ror of 117 m.In an effor t to overcome th e smal l B /H ra t io of ver t i -

ca l ER EP p h o to g rap h s , t r i an g u la t io n was p e r f o rmed o n

a two - s t r ip b lo ck o f o b l iqu e ly co n v erg en t p h o to g rap h staken over Paraguay (ref . 2-22). Horizontal accuraciesof appro xim ately 15 m and ver t ical accuracies of ap-p ro x imate ly 25 m were ach iev ed w i th an rms e r ro r fo rp h o to g rap h ic imag e measurements of 8 ^m. O n l y 10origina l g ro u n d co n t ro l p o in ts were m in im a l ly r equ i r ed

to acco mp l i sh t r ian g u la t io n ov er a 50 000-km 2 area;how ever , because of availab il i ty , 40 ground c ontro lpoints were used. This block had a B/H ratio of ap p ro x -ima te ly 0.9 and c onsisted of a ver tic al str ip of S190A

photographs f rom one ER EP o rb i ta l p as s and a s t r ip ofS190B photog raphs f rom a so lar iner t ia l pass f rom anadjacent orbit. During the S190B pass, the spacecraft

FIGURE 2-26.—Conceptual geometry of vertical S190A an d obli-qu e ly convergent S190B coverage o v e r Paraguay wi th a 0.9

base/height ra t io . The desig nator "PP" represents the pr i n c i pa lpoint.

w as o r ien ted (p i tch ed and ro l led ) su ch th a t th e S190Bcamera p h o to g rap h ed a lmo s t th e id en t ica l g ro u n d a reap h o to g rap h ed d u r in g th e S190A pass, as co n cep tu a l lyd emo n s t r a ted in f igure 2-26. This tr iangulat ion is cap a -b le o f su p p o r t in g p lan ime t r ic map p in g a t s ca les o f1:50 000 and s m a l l e r and t o p o g r a p h i c m a p p i n g at scalesof 1:100 000 and smaller.




Orig ina l Mapp ing Ac t iv i t i e s

The use of Sky lab ph otogr aph y to revise reconnais-sance maps of regions in Central America and SouthAmer ica was r epor t ed by Stap l e s et al. (ref. 2-22). In

G u a t e m a l a , a 1:50 000-scale p lan im etr ic m ap ( s h o w n in

reduced form in fig. 2-27 (b) ) w as produced f rom a pa i r

of S190B b l a c k - a n d - w h i t e pho tograp hs en l arged to 23 by23 cm (9 by 9 i n . ) , by using a stereoplot ter . Out l ines of

u r b a n areas , h ighw ays , r a i l roads , and na tu ra l f ea tu re swere mapped . A 2486-km 2 region in and around Con-c e p t i on , P a r a g u a y , w as p l a n i m e t r i c a l l y m a p p e d at a

scale of 1:100 000 by u s i n g a p p r o x i m a t e l y 25 pe rcen t ofth e stereomodel of two S190B 2 x en l argement s . A totalo f 36 man-h ours was expended on com pi l ing t h i s map .If aircraft pho tographs had been used, 50 stereomodelsand a ppro xim ate l y 250 man- hours w oul d have been re -qu i r ed to accompl i sh th e s a m e task .

A p l a n i m e t r i c map (scale, 1:100000) of Fundac ion ,Co l ombia , w as prepared from 29.2- by 29.2-cm S190B

c o l o r d i a p o s i t i v e s a n d a u n i v e r s a l s t e r e o p l o t t e r(Fletcher, ref. 2-22). A port ion of this m ap ( f ig . 2-28(b))shows th e location of the t r anspor t a t i on ne tworks ,other cul tural features, hydrographic features, andforests , as compared to a s imi lar map of this areapub l i shed in 1954 (f ig . 2-28(a)) . Topography on the

Skylab map was t ransferred from the 1954 map sheet . As i m i l a r m a p ( n o t s h o w n ) w a s c o n s t r u c t e d f r o m1:50 000-scale a i r c raf t pho tographs to serve as a basis ofcompar i son ; th e precision of the map prepared fromSky la b pho tographs was found to be w i t h i n acceptablel imi t s for the 1:100000 scale. W i t h use of the S k y l a bphotographs, the mapping of the 2400-km 2 area was ac-

compl i shed in 72 man-hours , a t ime e l ement approx-ima te ly 8 t imes less t han t ha t r equ ired fo r map p ing wi thuse o f the 1:50 000-scale a ircraf t pho tographs .

Despi te the poor B/H rat ios, ver t ical Skylab image ry

and t he previously ment ioned obl iquely convergentpho tographs we re used to produce topograp h i c maps of

p o r t i o n s o f t h e H i m a l a y a M o u n t a i n s , A r i z o n a , a n dParag u ay .

M o t t et al. ( ref . 2-24), us ing 2.5 X glass diaposi t ives ofvert ica l S 1 9 0 A p h o t o g r a p h s and a f ir s t -order p h o t o -g r a m m e t r i c s t e r e o p l o t t e r , p r o d u c e d 1 : 5 0 00 0 0- a n d1:62 500-scale maps, both wi th 250-m contour inter -

vals , o f p o r t i o n s of the r ug g ed H i m a l a y a M o u n t a i n s . Int h i s ana l ys i s , on l y t e chn iques a n d i n s t r u m e n t a t i o n c om -m o n l y used in c o m m e r c i a l m a p p i n g c o m p a n i e s w e r e

u s ed . T o p o g r a p h i c m a p p i n g w a s p e r f o r m e d b y Goetz etal . ( ref . 2-27) w i th the use of p ar t i a l f r ames of S190B col-or p h o t o g r a p h s of cen t ra l A r i zona ( f ig . 2 -29). A n

a na ly t i ca l p l o t t e r , con tac t d i apos i ti ve s , and g round con -t r o l f r o m 1 : 2 4 0 0 0 - a n d 1 : 6 2 5 0 0 - s c a l e U S G Sto p o g rap h ic maps were used to produce a 1:100 000-scale topographic map w i t h 150-m contours covering a57- by 66-km area of the Verde V a l l ey . A por t ion of t h i smap, at one-hal f scale , i s shown in figure 2-29(b ) . Theh igh ly conve rgen t conf igura t ion c rea ted by a vert icalst r ip o f S190A pho tographs coup l ed w i t h an obl ique-

lo o k in g st r ip of S190B pho tographs w as used to mapport ions of Paraguay for which reconnaissance m a p swere avai lable . A n analyt ica l p l o t t e r w as used to pro-duce 16 f u l l and 13 p ar t i a l t o p o g r a p h i c m ap sheets at ascale of 1:100 000 w i t h 200-m contour intervals . An ex-a m p l e of one of these m ap sheets , reduced to page size,is s h o w n in figure 2-30 and i l lust rates th e val ue fo r th ist y p e of ma pping ac t iv i ty .

An e xp er im enta l 1:250 000-scale ph oto ma p coveringth e s a m e area as the standa rd 1 ° by 2° topog raph ic sheetof Har t fo rd , Conn ec t i cu t , was p roduced by t he USGS.The mosa ic (fig. 2-31) was assembled from port ions offour S190A b l ack - and - wh i t e (0.6 to 0.7 / A I D ) frames by

us ing a p h o t o m e c h a n i c a l film mosaic process . A n o t h e rp h o t o m a p of the Hartford area w as prepared a t a

1:100000 scale wi th use of the S190B color-infrared(0.5 to 0.88 /nm) f i lm. Both p roduc t s meet nat iona l mapaccu racy s t a nda r ds fo r pos i t i ona l accuracy .




-0 G E O G R A F I C O N A C I O N A l

(a )

F IGURE 1-11.—Maps of Escuintla , Guatem ala, and vi c in i ty , (a) Conven t ional topographic map publi shed in 1973 at a scale of 1:50 000.(b ) P l a n i m e t r i c m ap compi led f rom S190B f rames SL4-89-290 an d SL4-89-291 obtained in February 1974.

6 8 S K Y L A B E R E P I N V ES TI GA T IO N S S U M M A R Y



G U A T E M A L A I 50.0OO E S C U I N T L A

Compiocior totogromit rica •toborodo cor lot 'mo»«n«iN. 69-2*0 f 89-294 Ml pfo*CtO SKYLAB imdg*n«tlomodo in liDr.ro lit 1974

( b ) ESCUINTL* G UA T E M A L A .

FI G UR E 2 - 27 . —C o n c lu ded .




1660000

Longtudes a paste de Greenwich

•* « Pantaoo

C*. Cienaga

At Arroyo

« Canada

Q. Oucbrada

^f Acequia

Arena

Aerodrome Case C

Panas tiK)roe(*c1ncas

Rancfia potjlicada en 1959

Vistas Kxnadas en e ano de 1994

DeclinacKn magnetic^ 0*23. 2 E- en et puno de co-

Ofdenadas X- 1.680.000 Mts Y-970.000 Mts dedu-

cida para 1959. 5 de mapa isogoncc de 1958.5

Vanaci6n anua - 56

nkxnertclabjra revsada t inas actuatzadas en 1959

0* Lit en e I. 3 A C

la] S c a l e , k m

10

FIG U RE 2-28.—Maps of Fundacion, Colombia , area , (a ) Convent ional topographic map pu b l i shed in 1954 at a scale of 1:100 000. (b )Planimetric m ap prepared in 1975from S190B color photograph. Topographic deta i l s were t ransferred from the map sho wn in f igure 2-28(a) .

7 0 S K Y L A B E R E P I N V E S T I G A T IO N S S U M M A R Y



Longtudes a Oeste de Greenwich

Pantano

Cyu Cienaga

.

Q

Ac

Canada

Ouebrada

Acequia

** Arena)

•^ Aerodfomo Case C

~£ Pantas hidroeectricas

V i\ s

k«.i\ ,

•>

•? / P l ipc f t l D u b h c M t a m IKq cno'atcifrifiM Tomcte in t< tno (

La Declmacibn M agnetica en el cenlro del mapa para 1 975

es de i« 45 9 dpducida de laCarta Isogoncade Coom-

bia para 1 970 Vanacion anual + 8 . 0

m *l tAo tt(959.

Eiti nu*vi idiciAn * h hcchauni/tnda IM mgnci tonwdti por K•Mliti SKY LAB. part Ktuiliw l«*«i di comumcacion ydtmK npiciapwimtncort* pa cutui.

Si undi i i f ic>bn tctul'iid tonmfrmdt SKY LA B

(b)

F I G U R E 2-28 .—Concluded .




(a) S c a l e , k m

FIGURE 2-29 .—Verde Valley, c en t r a l Arizona. Th e broad , flat valley dominates th e r igh t half of the area shown, (a ) S190B photograph

(SL4-90-30S). (b ) Topographic m ap prepared using photograph shown in figure 2-29(a). (Original scale, 1:100 000.)




\ S c a l e , km





H E R N A N D A R 1 A S

\

'

IGM-IAGS- NASA - ERO S HE «N AN D ABIAS . P A«AGUAV

FIGUR E 2-30.—A topographic m ap of a portion of Paraguay produced from a vertical S190A frame coupled w i t h an ob l i q ue l y

conve rge n t S190B f r am e . The map is a reduct ion of the 1:100 000-scale compi lat ion.




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In Canada, S tewart ( ref . 2-23) prepared a s a m p l ep h o t o m a p t ha t covered app rox im a te ly one - th i rd of astandard l:250000-scale map sheet. The S190B black-a n d - w h i t e data were rect i f ied d i rec t ly , in one stage, andprovided an exce l l en t image (3 .8x enla rgem ent ) basean d p l a n i m e t r i c a c c u r a c y . P ho t o m a p p i ng th e same areafrom s tandard aeria l photographs (1:36000 scale) re -quired 240 p r i n t s . W i t h an increase in the n u m b e r ofphotographic pr in t s requi red to cover an area , densi ty-and cont ra s t -ma tching prob lems , a s well as defects dueto b a nd i ng and tone co nt ro l , occur . Space pho tographssuch as those obtained from th e S190B system el iminateth e majo r i ty of these defects, and large areas can bem a ppe d by using rela t ively fe w space photographs .

A very p ract ica l feature of vert ica l S190A- andS190B-type data is the capabi l i ty for use as unc on t r o l l e dphotom aps . Ind iv idu a l f rames can be d i rec t ly en la rgedto the specific scale and fo rm at tha t perm its direct com-pa r i son be tween the en la rged ph otograph f rame and ex -

i s t ing l ine maps . Th e enlarged frame is re la t ive ly free ofdis tort ions , and po si t ioning to map c ontrol is more th anadequate fo r visual comparisons of changes in mapdetail . Photographs from th e S190B system have beenenlarged to the 1:24000 scale of s tandard topographicm a ps ( a pp r ox i m a t e l y 4 0 x e n l a r ge m e n t ) t o pe r m i tvisual com parisons of the cul tural changes th at have oc-cur red s ince the map was publ i shed .

Summary

Th e accompl i shments and results of the var ious

S kylab ER EP ca r tographic exper iments have demon-s tra ted the p otent ia l and the p ract ic al i ty of us ing qua l i typho tograph s f rom o rb i t ing spacecra f t a s a means of pre-pa r ing and up da t ing ce r ta in types of maps and o the rcar tograph i c produc t s . I t was clearly shown that , withsuitable spectral resolution and geometric f idel i ty ,photographs f rom space can serve as an adequate sourcefo r a var ie ty of ca r tographic produc t s at scales of1:100000 and smal l e r . W i th improved resolu t ion , th i sscale l imi t m i gh t b e i m pr ove d to 1:50000 or even1:24000. It was concluded that Skylab EREP space

p h o t o g r a p h s c a nno t c om p l e t el y s upp l a n t a ircraf t pho t o -g r a p h s an d gr ound - t r u t h i n fo r m a t i on fo r ca r tographicapplications at scales of 1:100 000 and larger. The needf o r c o n v e r g e n t p h o t o g r a p h s t o e n a b l e d e t a i l e dto p o g rap h ic m a p p i n g from space images w as de m on-s tra ted.

Litt le effort w as expended on inves t igat ing th espectral aspects of the Skylab imagery in ca r tographicappl icat ions. This area should be specifically m a r k e dfo r future s t udy .

To accomplish most cartographic object ives , c loud-free photograph ic coverage at repeated intervals is re-quired over most regions. Because of problems createdby weather , a satellite to ta l ly dedicated to c a r t og r a physeems to offer th e highest potent ia l fo r sat isfying thisneed. Such a sa tel l i te , w i th one or more high-resolut ion,l arge-format , long-focal - length cameras des igned top h o t o g r a m m e t r i c s tanda rds , would provide a prac t i ca -b le means of so lv ing man y t e r res tr i a l mapp ing prob-

lems. Such a sys tem wo uld prove especia l ly valuable fo rthe es tabl ishment and densif icat ion of ground control ,the construct ion of new maps and photomosaics in themore remote regions of the Ear th , and the revision and

u p d a t in g of ex i s t ing ca r tographic produc t s .

R E F E R E N C E S

2-1. An de r s o n , J . R. ; H a r d y , E. E.; and Roach, J. T.: A Lan d - Us e

Classification System for Use W i t h R em o t e Sensor D ata .

U.S. Geol. Survey Circ . 671, 1972.

2-2. H a n n a h , John W .; Thomas, G ar l an d L. ; and Esparza , Fer -

n an do : P l an n in g App l i c a t io n s in East Centra l Flor ida .

N A S A CR-145415, 1975.

2-3. Stoeckeler, E. G. ; W o o d m a n, R a y m o n d G.; and Farrel l ,

R o b e r t S .: Mul t i d i s c i p l i na r y An a ly s i s of Skylab P ho to g r aphy

fo r Hig hw ay En g in ee r in g P u rpo s es. NA SA C R - 141942 ,

1975.

2-4. Colw ell, Rob ert N .; Bowden, Leonard W . ; et al.: Use of

Skylab I mag e r y to Assess and Mo n i to r C han g es in the

Southern California Environment. NA SA CR-147561, 1974.

7 6 S K Y L A B E R E P I N V E S TI GA T I O N S S U M M A R Y



2-5. H o f f e r , Roger M .: C o m p u t e r - A i d e d A n a l y si s of Sk y l ab

Mul t i sp e c t r a l Scanner Data in Moun tainous Terra in for

Lan d Use, Fores try , W ater Resource, and Geologic A pp l i c a -

t i o n s. NA SA C R - 147473 , 1975 .

2-17. Polcyn, Fabian C .; R eb e l , D ian a L. ; and C o lwe l l , J o hn E .:

An a ly s i s of Hydrological Features of Por t ions of the L a k e

Ontar io Bas in Us ing Skyla b and A i rc r a f t D a t a . N A S A

CR-147456, 1976.

2-6. Poul ton , Char les E. ; and W elch, Robin 1 . : P lan for the

U n i f o r m M a p p i n g o f E a r t h R e s ou r ce s a n d E n v i r o n m e n t a l

C o m p l e x e s Fro m Sky lab Imag ery . N AS A CR-144484, 1975.

2-7. Har dy , E . E . ; Sk a l ey , J . E . ; e t a l . : En han c emen t an d Ev a lu a -

t ion of S k y l a b P h o t o g r a p h y fo r P o ten t i a l Lan d U se I n v en to -

r ies . NASA CR-144473 , 1975.

2-8. Co o per , Sau l ; An de r s o n , D u w ay n e ; e t a l .: Sk y lab I mag e r y :

Appl ica t ion to Reservoir Man ag emen t in New England.

NASA C R - 144514 , 1975 .

2-9 . Klem as , Vy tauta s ; Bar t le t t , David S. ; e t a l . : Sk yla b /E RE P

App licat ion to Ecological , Geological , and Oceanog raphic In-

ves t igat ions of Dela ware B ay . NA SA C R-144910, 1976.

2-10. Simonett , David S. : Ap pl ica t ion of Skylab ER EP Data forL a n d U se Man ag emen t . NAS A C R - 147457 , 1976.

2-11. Alex ander , Rober t H. ; and Lin s , H. F. , J r . : Selec ted A ppl ica -

t io n s o f Sk y lab H ig h - R es o lu t io n P ho to g r aphy to Ur b an Ar ea

Lan d Us e A n a ly s i s . NA SA C R - 13 9997 , 1974.

2-12. Baldridge, Paul E.; Goesling, P. H.; et al. : Utilizing Sk y l ab

Data in On-Going Resources M a n a g em en t Programs in the

State of Ohio. NASA CR-134938, 1975.

2-13. W elby , Char les W . ; and Lamm i, J . O. : Uti l i zat ion o f E R E P

Da t a in Geological Evalu at io n , Regional P lannin g , ForestMan ag em en t , an d Wa te r Man ag emen t in No r th C a r o lin a .

NASA CR-144104, 1975.

2-14. Silva, Leroy F. : A Study of the Uti l iza t ion of ERE P D ata

From th e W ab ash R iv e r Bas in . NASA C R - 147412 , 1976.

2-18. Sat t inge r , I . J . ; Sad owsk i , F . G . ; and Ro l ler , N. E. G . :

A na l ys i s o f R ec r ea t io n a l Lan d Us in g Sk y lab D a ta . NA SACR-144471, 1976.

2-19. Brooks , Ronald L. ; and Parra , Car los G. : Appl icab i l i ty of

Satellite Rem ote Sens ing for Detec t ion and M onitor i ng of

Coal Str ip Mining Activ i t ies . N A SA CR-144474, 1975.

2-20. W e ir , Cha r l e s E .; Powell , Richard L.; et a l .: Ap p l i c a t io n of

ER EP I mag er y to F r ac tu r e - R e la t ed Min e Safety Hazards in

C o a l Min in g an d Min in g - En v i r o n men ta l P r o b lems in In-

diana . NASA CR-144495, 1975.

2-21. And erson, R. R. ; Car ter , V. P . ; and Als id , L. J . : Skylab -

E R E P I n v e s t i g a t i o n s o f W e t l a n d s E c o l o g y . N A S A

CR-13 9224, 1974.

2-22. Staples , Jack E. ; Eold an , J . J . M. ; e t a l . : Overal l Ev aluat ion of

Skylab I mag e r y fo r M a p p i n g of L a t i n A m e r i c a . N A S A

CR-144476, 1975.

2-23. Stewart, R. A. : Inves t igat ion of Selected I mag e r y Fro mSkylab /EREP S190 Sys tem for Medium and Small Scale

M a p p i n g . N A S A CR-144542, 1975.

2-24. Mo t t , P. G.; Fu l l a r d , H.; et al . : Car tograp hic Research in

ER EP P r o g r am f o r Sma l l Sc al e M app in g . NA SA C R - 144478 ,

1975.

2-25. Colvocoresses, Alde n P . : Ov eral l Evaluat ion of Skylab

( E R E P ) I m a g e s fo r C a r t o g r a p h i c A p p l i c a t i o n . N A S A

CR-147 423, 1975.

2-15. G i l m er , Davis S. ; and W ork , Edgar A . , J r . : Uti l iza t ion of

Skylab ( ER EP ) Sy s tem fo r Appr a i s in g Cha n g es in Conti -

nenta l M igratory Bird Habita t . NAS A CR-1 47542, 1975.

2-16. Higer , A. L. ; Coker , A. E. ; Schmidt , N. F. ; and Reed, L. E. :

An An a ly s i s an d C o mpar i s o n o f Lan ds a t - 1 , Sk y lab ( S - 192) ,

an d A i rc r a f t D a t a fo r D e l in ea t io n o f L a n d - W a t e r Co v erTypes of the Green Swamp , F lo r ida . NA SA C R - 144855 ,

1976.

2-26. K el l e r , Mo r to n : An a ly t i c Aer o t r i an g u la t io n Ut i l i z in g Sk y lab

Earth Ter r a in C amer a ( S - 190B) P ho to g r aphy . NASA

CR-144387, 1975.

2-27. Goetz, A. F. H.; Ab r ams , M. J.; et al.: Co m p a r i so n of Sk y lab

and Landsat Images for Geologic Mapping in Nor thernArizona. NASA CR-147503 , 1976.




P a g e Intentionally Left Blank



Agriculture, Range, and Forestry

ROBERTN. COLWELL,af

F. PHILIP WEBER.b

A N D R Y B O R N R . K l R B Y 1 '

A ; R I C U L T U R I S T S , R A N G E M A N A G E R S , an d fores tersare p r imar i ly concerned w i th the managem ent of

resources such as crops , forage, l ives tock, t im be r, soi l ,and wa t e r . If wisely managed, these resources w i l l con-t inue to p r ov i de m a nk i nd with food, f iber , and she l t e r ;if they are not wisely managed, m a n ' s surviva l w i l l

become threatened. During the past 100 years, the ex-t en t of resource management and p r o d u c t i o n has ac-celerated r ap id ly . Resource managers have identif ied

the need for t ime ly and accura te informat ion on w ha t isbe ing produced; where it is be ing produced ; th e generals ta te of hea l th, or con di t io n, of the resource; and theamounts expected to be p r oduc e d .

In th e past decade, th e data acquired by spacecra f thave provided a new tool to assist in the de c i s i onm a k -ing processes of the resource managers . Th e pu r pos e of

this sect ion is to show , with spec if ic exam ples , how thedata acquired by the Ear th Resources Exper imentP a ck a ge ( E R E P ) can be used to satisfy some of the in-fo rmat ion needs of resource managers . Numerous in-ves t iga tors addres s ing d i f fe rent in form at ion requi re -ments submi t t ed f indings , and the m os t pe r t inen t ex -amples a re c i ted in th i s repor t . The E RE P inves t iga torshave demons t ra ted the capabi l i ty t o i nve n t o r y m a nydif ferent types of agr icu l tural , range, and fores tryresources . Th e resul ts show that th e f indings obtainedat their test sites ar e applicable to analogous areast h roughout the w o r l d .

a Un iv e r s i ty of Cal i forn ia a t B e r k e l e y .

''U.S. D e p a r t m e n t of A g r i c u l t u r e Fores t Service.C NA SA Ly n d o n B . J o hn s o n Spac e C en te r .

Princ ipal Inves t igator .

The wise management of Ea r th resources requi resi m p l e m e n t i n g a three -s t ep proces s : in ven tory , ana lys i s ,and opera t ions . In the in v en to ry s tep, an area-by-areade te rmina t ion i s m a de of the a m o u n t and q ua l i ty of theexist ing resources . In the an a lys i s s t ep , manag eme ntdecis ions are m a de with respect to the u l t i m a t e use ofth e resources after consideration of the type an d condi-t ion of the resources and the cost benefits. In the opera -t ions s tep, th e resource m anager implem ents each dec i -sion m ade in th e ana lysis phase; e.g. , the dec ision to ap-p ly th e a p p r o p r i a t e fertil izer in cer ta in mineral -def ic ientparts of an agr icu l tural area; the decis ion to pract icedeferred , rota t ion al grazing in certa in parts of a range-l and area; or the decis ion to cut only the overmaturetrees in a cer tain par t of the forest area. The resourcesare highly dynamic ra the r than s t a t i c ; to effectively

manag e them , a new inven tory mus t be ob ta inedper iodical ly (a process k now n as mo ni tor in g) .

D A T A R E Q U I R E M E N T S A N D A P P L I C A T I O N S

The types of information necessary fo r moni tor ingvegetation resources are provided in table 3-1. Federal,State, and county agencies, as well as in d u s t r ia l firms(identified in table 3-II) , use t h i s i n f o r m a t i on , w h i c h

cur ren t l y is largely obtained by means of ground sur -veys . A l thou gh re la t ive ly sma l l am oun ts of the resourceda ta are ob t a i ne d by remote -sens ing t echniques , the use

of such re mo tely sensed data has great ly increased dur-in g th e last decade. Satisfying th e requi rements for allthese users is compl ica ted because th e users wantdif ferent informat ion about vege ta t ion groupings in

79





d i f fe ren t places , a t different t imes , and w i th different

levels of accuracy . In addi t ion , they have d i f fe rent re -q u i r e m e n t s as to the speed with which vegetat ion infor-

m a t i o n m us t be processed after the raw data have beencol lected, and t he f requency wi th which th e i n f o r m a -t ion must be upd a ted ( t ab le 3 - I I I ) .

T h e E R E P investigators considered the remote-sens-ing capabilities that would be necessary to satisfy someof the resource info rm at ion requi rem ents in tab le 3-1,and, in this context , they analyzed the EREP data tode te rmine th e potent i a l fo r prov id ing needed inform a-t ion . A l though the pr im ary emphas i s was g iven tov e g e t a t i o n r e s o u r c e s , i t w a s r e c o g n i z e d t h a tagricul tur ists , range managers , and foresters are also in -terested in animal resources such as l ives tock andwild l i fe . Moreover, they are interes ted in the ent i recomplex of Ear th resources ( in clu din g soi ls , water ,minera l s , a nd a tmosphere ) in the areas fo r whi c h t he yha ve management respons ib i l i t i e s. In the fol lowing sub-

sect ions , the resul ts of the E RE P inve st igat ion s are pre-sented fo r most types of data required to monitorvegetat ion resources .

A g r i c u l t u r e

Recen t l y , agricul turis ts were asked to list th e specif icap p l ica t io n s of remote sensing tha t might prove profi ta -

ble in t e rms of cost /benefi t ra t ios and the tota l savingstha t might be achieved fo r each crop. In addi t ion to the

types of da ta show n in table 3-1, they selected th e mostimportant candidate problem in U.S . agricul ture—theextent of damage done each year to specif ic crops byspecific insects or pa t hoge ns .

Range

Range managers are concerned w i t h land manage-m e n t and w i t h anima l management on lands that pro-duce mature forage fo r a n i m a l (wild or domest ic) con-sumption. One of the major object ives of a range man-ager is m a x i m i z a t i o n of the produc t ion forage concur -

r en t with conservat ion of the land resources . In theUnited States , there are two basic types of range areas,fo r whi c h th e same resource informat ion is requi red .

T A B L E 3-III.—Frequency With Which Resource Information Is Desired

Time interval Agricultural crops Timber stands Range/and forage Other vegetation

(mainly shrubs)

10 lo 20 m i n u t e s

10 to 20 hours

10 to 20 d ays

10 to 20 months

10 to 20 years

20 to 100 years

Obs e rve ad vancing w a t e r l i n e inc rop lands d u r i n g disas trous f loods;

observe th e s tart of locust f l i g h t s in

a g r i cu l tu ra l areas

M ap p e r i m e t e rof ong oing f loods an d

locust fl ights ; moni tor th e wh ea t be l t

fo r o u t b r e a k sof bl ack - s t em r us t caused

by spore showers

M ap progress of crops as an aid to crop

id en t i f i c a t ion ( u s i n g " c r o p c a l e n d a r s " )

an d es t ima te d a l e t o begin h a rves t ing

ope ra t i ons

Fac i l i t a te annua l inspect ion of crop

Detect the start of forest fires Detect the s tart of rang elandd u r i n g p e r iod s wh en th e re

i s a h igh "fire-dangerr a t i ng"

M ap p e r i m e t e r of ongoing

forest fires

Detect s tart of insectou t b re ak s in t imber s t and s

f i r e s du r i ng p e r iod s wh en

t he r e is a h igh fire-danger

r a t ing


rangeland f i res

Up d a te i n f o r m a t i o n on range

readiness fo r graz ing

Faci li tate a n n u a l i ns p ec t ion Fac i l i t a te a n n u a l i ns p ec t ion of

rotat ion an d comp l i ance w i th Fed era l of f i rebreaks

re qu i r e me n t s f o r benef i t p aym ent s

Observe growth an d mortal i ty rates ino r c h a r d s

Obs erve s h i f t i n g cu l t i v a t io n p a t t e r n s

Observe growth an d

m or ta l i ty rates in t im ber

s tands

Obs erve p l a n t success ion

t rend s in t imber s t and s

f i r eb r eaks

Obse rve signs of ranged e te r io r a t ion a nd s tud y th e

spre ad o f nox ious weed s

Observe p l a n t success ion

t rend s on range l and s

Detect th e s t a r t of br us h f ie ld f i resd u r i n g periods wh en there is a

h igh f i r e -d anger r a t i n g


brushf ie ld f i res

U p d a t e in for m a t ion on t i m e s of

f lower ing an d p ol l en

p r o d u c t i o n in r e l a t ion to the

be e i n d u s t r y and to hay fever

problems

Fac i l i t a te i ns p ec t ion of f i rebreaks

Observe changes in "edge effect"

of brushf ie lds that affec t

s u i t a b i l i t y as a w i l d l i f e h a b i t a t

Obs e rve p l a n t success ion trends

i n br us h f ie ld s

A G R I C U L T U R E , R A N G E , A N D F O R E S T R Y 8 1



These areas are (1) Federal and p u bl i c l y owned l ands

and (2) State and pr iva t e l y owned g rass lands . TheFederal and p u bl i c l y owned lands are located p r i m a r i l y

in the 17 W estern States and are managed by the U.S.G o v e r n m e n t . Th e State and pr iva te ly owned l ands a regeneral ly east o f t he Rock y Mou nta ins and a re managed

by Sta te gove rnment s and /o r p r iva t e owne rs . The m a n -agers for both types of areas have the s a m e object ives,and t he i r management e f fo r t s a re gove rned by t he i n -f o rmat io n r equ i rement s g iven in table 3-1. Satisfying

these object ives requires cont inual moni tor ing of al lvegetat ion to avoid forage waste , overgrazin g, anddamage to the range resources. The p r i v a t e o w n e r ac -qu i re s t h i s i n fo rm at ion by f requen t i n s i t u obse rva t ions ,but managers of the larger , p u bl i c l y owned l ands cano n ly i n spec t r ep re sen ta t ive po r t i ons and ex t rapo l a t e t hein f o rmat io n obtained from sample areas to other near-by reg ions . Th is ex t rapo l a t ion is difficult and unre l i ab l ebecause of the m any u nkn ow n fac to r s , i nc l ud ing ra in -

fall pat tern s, vegetat ion di fferences, and hab i tats ofl ivestock and wild l i fe .

Forestry

Foresters need essent ial ly th e s a m e i n fo rmat ion ( t a -b le 3-1) as that required by agr ic ul tur ists and range m an-age r s . Us ing a somewhat d i f fe ren t approach, forestersind i ca t ed t ha t r emote sensing can be especial ly he lp fu l

b y p r o v i d i n g i n f o r m a t i o n o n w h i c h t o base mul t i p l e -usedecisions re lat ive to each par t of the forest . The m u l t i -

ple-use concept is c o m p l e x and more app l i cab l e toforest ry than t o ag r i cu l tu re . Some foresters prefer toh a v e al l par ts of an area managed wi th respect to max-imiza t ion of t imbe r p roduc t ion ; o the r s wan t to preserveth e forests as p r i m e v a l m u s e u m s to be enjoyed in per-p e t u i t y . Between these tw o extremes a re those w ho con-d o n e each of these uses fo r specif ic par ts of a forest ifsuch use does not in terfere wi th the use of the forestp r imar i ly as a source of water fo r domest ic use andmine ra l s fo r i ndus t r i a l use and the preservat ion ofesthe t ic qual i t ies fo r recreational use. To s u p p o r t in -te l l igent decisionmaking processes regarding th e bestuse of each par t of the forest , two major types of infor-

mat ion are needed: (1) a resource m ap that accurate lydel ineates th e forest vegetation and a l l associated

resources (soi ls , wa ter , minerals , e tc .) and (2) adequatesociological , economic, and technological data to ensuretha t th e forests c an produce " the greatest good for the

greatest num ber ." Forest ry ap pl ica t ions addressed onlythe first of these two com pl ex and in t e r re l a t ed r equ i re -m e n t s , a resource m a p o f forested areas. Th e au thors ofthis section be l ieve tha t ma nagem ent techn iques can beenhanced by the use of space -acqu i red in fo rmat ion ,w h i c h will assist th e l arge-area manag er in d e c i s i o n m a k -

in g processes.

I N V E N T O R Y B Y P H O T O I N T E R P R E T A T I O N

A p r i m a r y o b j e c t i ve of this section is to discuss th eexten t to w h i c h E R E P d a t a wil l satisfy th e i n f o r m a -

t iona l needs of var ious users in the fields of a gr i cu l tu re ,

r ange management , and fo re s t ry . Th e E R E P i n v e s t ig a -tors ident if ied t he t yp e o f da t a and ana l ys i s t e chn iquestha t wou l d p rov ide t he r equ i red i n f o r m a t i o n fo rre source manag ement . Th e use fu l ness o f t he i n fo rm a-

t ion was eva l ua t ed in t e r m s of t y p e of data , fr equenc y ofobserv at ions, need for anc i l lary data, and me thod ofusing the data for resource management decisions. TheER EP inves t iga to r s , bo th dom es t ic an d fo re ign , haved e m o n s t r a t e d t h e c a p a b i l i t y t o i n v e n t o r y m a n ydifferent resources w i t h i n th e d i sc ip l ine s of agr i cu l tu re ,r ange management , and fo re s t ry .

Crop and Acreage Inventory

Agricu l tural l and use and c rop -p roduc ing areas arediscernible in photographs taken w i th t he M ul t i spec t r a lPho tograph i c Camera (S190A) and the Earth TerrainCam era (S190B) whe n t he pho tograp hs a re ana l yzed bys t andard pho to in t e rp re t a t i ve t e chn iques . Th e c ropsident if ied were c i t rus, coffee , sugarcane , and wheat .

The S190B color an d co l o r - in f ra red pho tographs ofthe R io Gra nde V alle y, enlarged to a scale of 1:63 000,were projected onto a standard view ing screen, resul t ingin a scale of 1:10000 ( H a r t et al., ref. 3-1), and in-te rpre ted by an agr ic ul tura l ana lyst to ident ify vegeta-t iv e pat t e rns and to discr iminate c i t rus, sugarcane , a ndcrops grown in larger fields. This data format ( f igs.3-1 (a) and 3-1 (b)) , w hen supp orted by t ransect low-a l t i tude-a ircraf t data (fig. 3-1 (c) ) and ground t ruth ( f ig .3-1 (d)) , provided the informat ion required for a f ie ld-

by-f ie ld i n t e rp re t a t i on . W hen co l o r - in f ra red pho to -g raphs we re ana l yzed , on l y annual c rops and fallow

l an d were ident if ied wi th 1 00 pe rcen t a ccuracy . C i t rus

8 2 S K Y L A B E R E P IN V E S T IG A T IO N S S U M M A R Y



Fal low land

C a n a l

site

Sugarcane

Home

site

- W e t

Pas ture

(d)

S u g a r -

cane

Fal low

land

Pastu re

- P o o r stand

W i n te r oats

J

Sugarcane

Oats

-Poo r

stand

Fal low land

S . P .

K

Scale, km

F I G U R E 3 - 1 . — A n i n t e n s i v e a g r i c u l t u r a l a r e a n e a r W e s la c o , Tex as , w i t h m a j o r c r o p s o f s u g a r c an e , c i t r u s , a n d v eg e tab l e s ,

(a ) S190B c o lo r - in f r a r ed pho to g raph t ak en J an u a r y 28 , 1974 (SL4-93-326). (b ) S190B color photograph taken D e ce m be r 5 , 1973 (SL4-91-005).( c ) A i r c r a f t c o lo r - in f ra r ed ph o to g r aph , (d ) G r o u n d - t r u th map . Th e abbrevia t ion P .C. indicates poor cov er; S.P., soil p a t t e rn .




was ident if ied with an accuracy of 93 percent when col -or- infrared film was used an d with an accuracy of 80percent when convent iona l co lor f i lm was used .Howev er , when both f i lm typ es were ana lyze d concu r -r en t l y , ci t rus w as i dent i f i ed w i t h 100 percent accuracy .This an alys is ident if ied the areal extent of fros t damage

to suga rcane growing in the test area.The areal extent of fros t damage in July 1973 (de

Mendonca et a l . , ref . 3-2) to the coffee of Maringa,Parana, Braz i l , was assessed us ing a mul t i l eve l survey -in g system in wh ich Landsa t , Sky lab , l ow-a l t i tudeaircraf t , and f ie ld vis i ts were the in f o rmat io n sources .A n S190B high-resolut ion color photograph (f ig. 3-2(a))acquired on Augus t 8, 1973, w as used to de l inea te th ecoffee- and whe a t -g r owi ng areas (fig. 3-2(b)) and toserve as a t ra ining area fo r ana lys i s of Landsa t com-p u t e r - c o m p a t i b l e t a p e s u s i n g a n i n t e r a c t i v emul t i spec t r a l image analys is sys tem. Th e descriptor ,w h i c h enabled i den t i f i ca t ion of the two crops , was the

cu l tu r a l pat ter n sh ow n in f igure 3-2(a) . The analy s is , inw h i c h class if icat ion resul ts based on mult is tage sam-p l in g were used, ind ica ted tha t 852 884 hm

2(2 107 522

acres) of fros t -affected coffee, 33864 hm2

(83680acres) of norm al coffee, and 302 342 hm

2(747 103

acres) of whea t were present in the study area. Thismul t i l eve l survey of a m a jor agr i cu l tura l com mod i typrovided a rapid assessment of the economic losses sus-ta ined from an act of nature .

W hen a st a t i st i ca l approach was used to inve ntory anagricul tural area for crop typ es and acreage, color andcolor-infrared ph otogr aph s in a 23.0- by 23.0-cm forma twere used to i den t i fy th e differing cul tural pat terns ors t ra ta and were out l ined direct ly on the wo rk ing da ta .

Th e photographic t ex ture , tone, color , pat tern, s ize ,shape , shadow, loca t ion , and associa ted features wereused to identify a s t ra tum (a large homogeneous area)(Colwel l et al., ref. 3-3). The t ex tures ( coa rse , me diu m,and fine) (f ig. 3-3) were indicat ive of the field sizes inth e areas of interes t . From experience, th e ana lys tk n o w s that a coarse texture (65- to 32-hm

2(160 to 80

acre) field size) indicates a predominance of field crops ,a med ium tex ture (12- to 32-hm

2(30 to 80 acre) field

s ize) indicates a m i x t u r e of field and vegetable crops ,and a fine texture (4- to 12-hm

2 (10 to 30 acre) fields ize) indicates vineyards and pastures . Color and color-infrared pho tographs f rom the S190A sys tem, en la rged

to a scale of 1:805 000 (20.3 by 20.3 cm), provided ascale that was considered opt imum for this task.

Color wi th in each s t ra tum indica ted the c rop typeand degree of ma tur i ty . Based on ph otogra ph ic t ex tureand color , areas were identif ied in which to obtaing r o u n d - b a s e d t r a n s e c t s for the d e v e l o p m e n t o fagricultural s ta t is tics (acreage, crop typ e, crop mat ur i ty ,irr igated fields, etc.). The image analyst used these

statistics to pe r f o r m s t r a t um -b y - s t r a t um i nve n t o r ie s fo rcrop acreage and crop class. (Classes we re m atu re or im-m a t u r e fo r whea t , ba r l ey , and safflower.) When th i sprocedure was used, s a m p l i ng efficiency was increased,classification errors were reduced, and an agr icu l turals t r a tum i n v e n t o r y w as achieved with an accuracy of 10to 20 pe r c e n t at the 95-percent -conf idence l eve l , wi th acost reduc t ion of 1 5 to 1 (ref. 3-3).

Acreage measurements of three land use categorieswere made by using s tereoscopic s tudy and image mag-nif ica t ion of the S190A and S190B ph otograp hs . W henth e S190A photographs were en la rged (20x) , fores t ,ba re so i l , a n d w e t l a n d s w e r e r e a d i l y i d e n t i f i e d .

1

General ly, th e S190A pho tograph s were s a t i s fac tory fo rin terpret ing gross characteris t ics only at the regionallevel . Major boun daries , such as roads and sect ion l ines ,could not be ident if ied. W hen forests and generalizedcrop categories were del ineated by us ing la te-summerphotographs or the mos t c loud-f ree photographs , ac-curacies of 93 and 94 percent , respect ively, wereachieved. The qual i ty of the S190A photographs ac -quired over a M ichigan tes t s i te was highly variable be-tween passes and f i lm/f i l te r c om b i na t i ons and betweend u p l i c a t e s of the f i l m s t r i p s . T h e r e s o l u t i on w a smarginal for purposes of crop acreage es t imation.Analysis of S190B b lack- and -w hi te photographs ac -quired from this same Mich ig an test site in late summer

indicated tha t sect ion l ines , roads , and field boundarieswere readily vis ible because of the imp roved resolut ionof the sensing sys tem. The acreage measurements wereperformed on magni f i ca t ions of 15 X, with an oculargrid ha v i ng a 0.25-mm l ine spacing.

W hen s te reoscopic and image magni f i ca t ion pro-cedures were used to estimate th e acreage of 170 fields,there was a tendency to underes t imate the acreage offields larger than 4 hm

2(10 acres) and a tendency to

overes t imate on fields smal ler than 4 hm2

(1 0 acres).

Leste r V . M a nd e rs ch i e d , "E conom i c Evalua t ion of C r o p AcreageE s t i m a t i on by Mul t i sp e c t r a l Re m ot e Sensing," EPN 472-11, Mich.

S t a t e U n i v . , D e p t . o f Agr icul ture Economics , East Lansing, Mich . ,1975.






23 ° G O ' S

52°00'W

10

Scale,km

FIGURE 3-2 .—Concluded .

Even wi th these biases , an aggregated percentage errorof 6 percent below the actual acreage in the test si te wasachieved. The resolut ion obtained by the S190B systemw as judged to be adequate fo r crop acreage assessment

fo r m a j o r field c r o p s , bu t f u r t h e r i m p r o v e m e n t inresolut ion wil l be useful for crops, such as vegetables,that are often grown on small plots.

Ana lysis of Digi t ized Photograp hs

Automat i c da t a -p rocess ing t e chn iques we re used in

the ana l ys i s o f E R EP pho tograp hs conve r ted to a d ig i ta lf o rmat to d e t e r m i n e th e exten t to which agr i cu l tu ra l in -f o rmat io n could be extra cted (C olw ell et al ., ref. 3-3).The four bands o f S190A b l ack - and - wh i t e pho tographs

acqu i r ed over th e Sal inas Val ley of Cal i fo rn i a dur ingth e Skylab 2 and 3 missions were digi t ized wi th amic rodens i tome te r and stored on magnet ic tape . Thes c a l e o f t h e p h o t o g r a p h s w a s a p p r o x i m a t e l y1: 2 850000, and the scan interval along the X - and Y-axes was 0.0254 cm with an aperture setting of 0.00254cm. The resulting resolution cell represented a 0.45-hm2

(1 .12 acre) area on the ground. Actual scanning t imewas 0 .5 hr /b and , w i th 0 .5 hour for se tup, for a total t imeof 2 .5 hours to digi t ize four band s of data.

The m agnet ic tapes were reform at ted to be com pat i -ble w i t h a com pute r p rogram th a t used a f ive-s tep pro -

cedure to ident i fy th e predominan t c rops p re sen t in thevalley ( i .e . , tomatoes, carrots , l e t tuce , asparagus, andca u l i f low er ) . Because tomatoes and le t tuce were in dis-t inc t stages of development dur ing the September




Scale, km

F I G U R E 3-3.—Southwestern S a n Joaquin V a l l e y , C a l i f o r n i a , J u n e 3 , 1973. Land u se s t r a t a ( f i g . 3-3(b)) a re c o r r e l a t ed f a i r l y w e l l w i t h th e

b o u n da r i e s b e t w een t he v a l l e y b as i n an d v a l l e y b as i n r i m soils a n d w i t h t h e b o u n d a r i e s b e t w e e n t h e a l l u v i a l an d b ed ro c k soils ( f i g . 3-3(a)).

H o w e v e r , t h e b o u n d a r y b e t w e e n t h e v a l l e y b as i n r i m s o i l s an d t he a l l u v i a l fan s o i l s does n o t c o r r e l a t e w i t h a n y o f t h e a g r i c u l t u r a l l a n d u s e

strata b o u n d a r i e s , (a ) N a t u r a l c o l o r S190A pho t o g raph ( SL2- 04 - 121 ) . B o u n da r i e s b e t w een m a j o r s o il t y pes hav e b een t r an s f e r r e d f ro m a soil

m a p . R e d c ro s s ha t c hed areas represent th e v a l l ey b a s i n soils, b l u e h a t c h i n g s h o w s th e v a l l e y bas in r im soi l s , a n d y e l l o w h a t c h i n g c o r r e l a t e s

w i t h th e a l l u v i a l fa n soils. U n h a t c h e d areas r ep re s en t soils t h a t d e v e l o p e d o n b ed ro c k m a t e r i a l , (b ) F a l s e - c o l o r - i n f r a r ed S190A p h o t o g r a p h

s ho w i n g l an d use strata (SL2-03-121).

Skylab 3 overpas s , they were fu r the r divided into twosubclasses: i m m a t u r e and m a t u r e .

The i n i t i a l analysis program s tra t i f ied th e test areaand produced gray-scale m a p s of discrete features toassist in the selection of t r a i n i n g areas fo r t he comp ute r .W i t h use of the t r a i n i n g area , statistics for classifying

each s t ra tum were de r ived , i d en t i fy in g th e mea n d en -s i ty, the s tanda rd d ev ia t io n , t he spec t rograms , and the

hi s tograms fo r each field and class of each b a n d ; cor -re lat ion and covariance matr ices were developed fo reach field and class for all b a nds . A n o p t i m i z a t i o n ofth e c o m b i n a t i o n of d a ta b a n d s w as p e r f o r m e d to give






T A B L E 3-1V.—Recognition Signature Bands

Training set,

no . of sections

(a )

40

20

B a nd

( b )

I

67

11

10

-9

3

6

1

1 1

12

ID

x

9

3

71 1

1210

aEach section within a training set represents 2 .6 km- (1 s . mi-')

bSee table 3-VI for band wavelengths.

The select ion process was one of ei ther select ingdif ferent bands o r d i s c r imina t ing be tween tw o data out-p u t s w i t h i n a discrete data band. The p rocess was one ofdata source select ion in w h i c h the 22 da ta outpu t s ( tab le3-VI) were d i sp l ayed on a t e l ev i sion mo ni tor to screenout data outputs that were unusable because of sa tura-

t ion or high sys tematic noise . Three data outputs fromthe re m ain ing data of each area of interes t were dis-p layed on a color moni tor , and the t r a in in g a rea wi th ineach s t ra tum of interest w as ident if ied. A grid coordi-na te tha t was d i sp l ayed s imul taneous ly on the mon i torassisted in locat ing th e t r a in ing sets.

W hen a complex agricul tura l scene west of Fresno,Californ ia (fig. 3-4), w as ana lyzed , an overal l c lass if ica-t ion accuracy of 81.8 percent and an average perfor-mance, by class , of 78.9 percent were achieved. Duringth e ana lys i s of a less com plex agr icul tu ral s t ra tu m (i.e. ,w h e a t , bar l ey , and safflower in an ann ual grass region ofth e Pacific coast ra nge ), a sign ifica nt increase in ac-

curacies w as achieved. For an area in the western SanJoaqu in V a l l ey , c l a s s i f i ca t ion accuracies of 100,100, and

98.6 percent were achieved fo r whea t , ba r l ey , andsaff lower , respectively; and class designations in eachcrop type were ident if ied.

W hen analy s is for the selection of the op t imu mbands for crop class if icat ion was perform ed on the 22

reclass if icat ion and s igna ture ex tens ion for the di f fe rentsignatures are l isted in table 3-V. Ini t ia l observat ionsindicate an except ion to the rule that the more t ra iningsets used for s ignature development , the higher the ac-cu racy of class if icat ion. A s given in table 3-V, sig-natures developed from the 20-sect ion t r a in ing setachieved a bet ter performance accuracy. This accuracyis a resul t of the procedures fol lowed when developingth e s ignatures from th e 40-section tra in in g set, in w h i c hmore s ignatures were com bined or dropped in the initial

signature-analysis procedures .

Man/machine in te rac t ive ana lys i s of the S192 datawas performed by Colwell et al. (ref. 3-3), by using al lthe 22 data outputs from the 13 channels . The a nalys isprocesses were th e same as those described in the dis-cuss ion of the an alys is of digi t ized ph oto grap hs , exceptthat there w as a larger array of data chann els ( table 3-V I ) . An op t imiza t io n program ident i f i ed the bands of

data m ost ap pro pria te for class if icat ions of the scene.

TABLE 3- V.—Accuracies Achieved

for Crop Classification

Training set, Classificationno . of sections accuracy, percent

Reclas s i f i ca t ion3

4 0

2 0

10

70.0

75.1

67.0

Signa ture extension13

40 63.0

aOny reclassification of the 40-section training set area was performed using the sig-

natures deveoped from each of the respective training sets.

^For signatureextension.48sections in thesouthern portionof the test area were evau-

ated using signatures deveoped from the 40-section training set in the northern portion of

the test area.




TABLE 3- VI.—SI92 Spectral Bands

Used in the 22-Feature Format

;

Scale, km

Y e l l ow - Mature barley

R ed - TomatoesWhite - Cotton

O r a n g e - Fallow

Pink - P otatoes

Purp le - C uc umbers

A q u a - Barley stubbleBlue - Sa f f l ow e r

Green - Al fa l fa

Black - O t h e r

Band

\

2

1

4

5< .-

8

9

i n

1 1

i :

13

L 3

3

45

6

7

1 !

12

13

Spectral

feature

(a )

1

:34

56"

s

9

i n

1 1

12

1 3

14

15i f ,r18

19

20

2 1

2 2

W avelength.

A- "

0.41 to 0.46

0.46 to 0.51

0.52 to 0.56

0.56 to 0.61

0.62 to 0.67

0.68 to 0.76

0.78 to 0.88

0.98 to 1.08

1.09 to 1.19

1.20 to 1.30

1.55 to 1.75

2. 10 to 2.35

10.20 to 12.50

10.20 to 12.50

0.52 to 0.56

0.56 to 0.61

0.62 to 0.67

0.68 to 0.76

0.78 to 0.88

1.55 to 1.75

2. 10 to 2.35

10.20 to 12.50

Description

Violet

Violet -b lue

Blue-green

G reen - y e l l o w

Or an g e - r ed

R ed

Reflectance

infrared

Reflectance

i n f ra red

Reflectance

inf rared

Reflectance

inf rared

Reflectancei n f r a r e d

Reflectance

infrared

T h e r m a l

i n f ra red

T h e r m a l

inf rared

Blue-green

G r e e n-ye l l ow

Or an g e - r ed

R edReflectance

infra red

Reflectance

i n f ra red

Reflectancei n f ra red

T h e r m a l

inf rared

Sampling

scheme

(b )

Low

Low

High od d

High od d

High od d

High od d

High od d

Lo w

Lo w

Lo w

High od d

High od d

Lo w

High o dd

High e v e n

High ev en

High e v e n

High ev en

High e v e n

High e v e n

High ev en

High e v e n

aln the context of the discr iminan t analys is of remote-sensing data, a feature is any con-

t i n u o u s function over a specified range t h a t describes a par t i cul ar p o i n t or area on the

ground. In part, th i s func t i on ma y cons i s t of spectral data (e.g., mul t i spect ra ! data or digitized

m u l t i b a n d photographs) , t extu ra l data genera ted from th e spectral data , or nonspec t ra l data

(e.g., topography, r a i n f a l l , or soil type) .

^The 13 S192 bands were s a m p l e d at 2 ra tes : lo w (72.6m ) center - to-centerspacing an d

high (36.3 m ) center - to-center spacing. On the digital tapes, th e high sampled bands were

hand led as e i the r an odd or an even low-ra te b a n d .

FI G UR E 3 - 4 .—C o mpu te r c l a s s i fi c a t io n o f a c o mplex ag r i c u l tu r a l

area wes t of Fresno, Cal ifornia , by analys is of S192 data . The datawithin th e black rec tangular boxes were used to t ra in th e au to ma t i c

c lass if ier , (a) Class if ied us ing a medium threshold for analys is .

(b ) Class if ied us ing a f ine threshold for a n a l y s i s .

9 0 S K Y L A B E R E P I N V E S T IG A T IO N S S U M M A R Y



features of the S192 d a ta , 4 spectra l features were

selected . They were (1) the h igh-density yel low data

o u t p u t , ( 2 ) o n e o f t h e h i g h - d e n s i t y r e f l e c t a n c e -infrared d a ta o u tp u ts (7 or 19), (3) one of the t h ree low-

d en s i ty r e f lec tan c e - in f r a r ed d a ta o u tp u ts (8, 9, or 10),

and (4) one of the h ig h -d en s i ty r e f lec tan ce - in f r a r ed

data outputs (11 or 20). S tu d ies in d ica te th a t wh en dis-c r i m i n a n t an a lys i s tech n iqu es are a p p l i e d to mo re th an

four b a nds of data , th e cost becomes p r o h i b i t i v e (i.e. ,

th e cost of an a lys i s in cr eases ap p ro x imate ly by thesquare of the n u m b e r of ban d s used) w i t h o u t signifi-

ca n t ly imp ro v in g th e c la s s i fica t io n accu racy . Th e S 1 92n ar ro w sp ec t r a l b a nds ap p ea r to p ro v id e mo re useful in -

f o rmat io n fo r d isc r imin a t in g amo n g c ro p typ es but re-quire precise t im ing for h igh ly d y n am ic c ro p typ es su ch

as vegetables.

SOILS

Soil is the basic medium fo r susta in ing th e p l a n t ,

an im a l , in sec t , min era l , an d h yd ro lo g ica l ecosystem onw h i c h m an d ep en d s for his existence. The basic soil

units were m a p p e d b y using th e s tan d a rd EREP p h o to -

graphic products , and t he so il sa l in i ty character is t ics

were d iscr iminated by analysis of the spectral datarecorded by the S I9 2 in s t ru men t . Th e q u a n t i t y of free

wa te r in the soil and of crys ta l l in e mo is tu r e in snow w asmeasured by the use of micro wav e d a ta .

Map p in g b y Photo in terp re ta t ion

The S190A an d S190B color an d color - inf raredp h o t o g r a p h s w e r e a n a l y z e d v i s u a l l y t o d e l i n e a t er e g i o n a l v e g e t a t i v e p a t t e r n s i n d i c a t i v e o f t h ea gr i cu l tu re , th e h yd ro lo g y , th e soil resources, and t he i n -sect h abi ta t s of a citrus-prod ucing area . W hen th e S190B

photographs were en larged to a 1:63 00 0 scale and pro-

jected for a subsequen t en la rg emen t to 1:10000,ag r icu l tu r e analysts (Har t et al., ref.3-1) identified hos tp lan ts an d p lan t d i s t r ibu t io n s , wh ich are the avenues ofcitrus- insect migration between Mexico and the Texasc i t r u s be l t . S u p p o r t iv e in f o rm at io n i d en t i fy in g p h y s i c a l

features of the area such as drainage patterns , water -

courses , and s o m e so il character is t ics w as der ived f rom

th e S190A photographs .Soil u n i t s and d ra in ag e p a t te rn s were map p ed by de

Men d o n ca et al. (ref. 3-2) on S kyl ab p h o to g rap h ic d a ta

of Camp o Gran d e , Mato Grosso, Brazi l . Th e S190A col-

or - inf rared f i lm ( f ig . 3-5(a) ) was used to separate and

m ap e ig h t typ es of soil ( f ig . 3 -5 (b ) ) . This m ap d er iv ed

from the S190A data co incided with the current so il

map o f th e a r ea ( f ig . 3 -5 (c ) ) , wh ich w as p r ep a red by th euse of ground transects . The map der ived f rom th e

S 1 9 0A p h o to g rap h ident i f ied th e v eg e ta t iv e p a t te rn s ,th e e x t e n t of good-qual i ty so il , and t he e x t e n t of h u m a n

ex p lo i t a t ion of the reg ion . Using th e same t y p e of d a ta

(fig. 3 - 6 ( a ) ) , Banner ! (ref. 3-4) map p ed p ed o lo g ica l

u n i t s in th e P ro v in ce o f Co r r ien tes , Arg en t in a (fig.

3-6(b)) , that compared f av o rab l y with so i l d e l in ea t io n s

on the soil map of the world (1 :5 000 000 scale ).

Salinity Disc r imina t ion by An a lys i s of S192 Data

Vegetated areas that exhibited d if ferences in qu an -tity and qu a l i t y of reflectance as co mp ared wi th th eref lectance f rom bare so il were analyzed through dig i ta l

processing (W iegand , ref . 3-5) , and t he resul ts were cor-rela ted with f ield measurement of the electr ical conduc-

t iv i ty of so ils of varying sa l i n i t y . Data were acquired by

th e 13-band SI92 scanner , and an a lys i s w as m a d e byl inear correla t ion in each d iscrete band . As the ref lec-t ance ra t io between vegetated areas and bare soil in -creased (i.e., as m o r e ref lectance w as received from th evegetat ion), th e sal in i ty level of the s tudy area was ob -

served to be lower . The correla t ions for the six con-

t in u o u s ban d s (6 to 1 1) in the wavelength reg ion of 0.68

to 1.75/xm were -0.739, -0.946, -0.862, -0.876,

—0.963, and —0.722, respectively.Veg e ta tiv e p a t te rn s , as extracted f rom th e S190B c ol-

or and co lo r - in f ra r ed p h o to g rap h s , were used to i d en t i fysubter ranean f reshwater levels in the pampa region ofArg en t in a (Ban n er t , ref. 3-4).In the area of investiga-

t ion , ground water occurs at the surface and to a d e p t h

of 20 m. On the ground, surveys revealed rela t ionships

amo n g th e mo rp h o lo g y , th e d ep th , and the sa l in i ty ofg ro u n d wa te r . These features on the E a r t h ' s surface canbe observed in EREP co lo r - in f r a r ed p h o to g rap h s ( f ig .4-26(a) in sec. 4) . These areas ar e delineated on ag ro u n d -wa te r -d ep th m ap (fig. 4-26(b) in sec. 4); thereg ions with a ground water table a t a d ep th of less thana p p r o x i m a t e l y 5 to 7 m ap p ea r l igh t blu e and are ch a rac -

terized by h ig h ev ap o ra t io n and increased soil a ndg ro u n d wa te r s a l in i ty , wh ic h lead to u n f av o rab le co n d i -

t io n s fo r cer ta in p lan t species and to sparse vegetativecover . These regions a re f av o red p r ed o min an t ly b yh a l o p h y t e s .






5 5 ° 0 0 ' W

20°00'S

5 5 ° 3 0 ' W

20°30'S

\ 010

Scale, km

(b )

Exp lanat ion

1 A re a s of i n tens ive a g r i c u l t u r a l activ i ty

with large-scale plantat ions predominant

2 A re a s of in tensive agr i cu l tu ra l act iv ity

w i th smal l -scale plantat ions predominant

3 R e la t i ve l y unexplored forest areas

F I G U R E 3 -5 .—Co n t i n u ed .

4 In tens ive ly exp lo red c leared pastu re land

5 R e la t i ve l y unexp lo red areas of cerradao vegetat ion

6 R elat ive ly unexplored areas of cerrado vegetat ion

7 R e la t i ve l y unexp lo red areas of vary ing topography

with cerradao veg etat ion predominant




55°00'W

20°00'S

55°30'W

20°30'S

\ 010N

Scale, km

E xplanat ion

a Small-scale ag r icultura l area

A Large-scale agricultura area

P C leared pasture land

Cd Cerrado vegetation

F IGURE 3 - 5 . —Conc lud e d .

C Cerradao vegetat ion

F Forest vegetation

Ci Nat ive rangeland

Q Burned areas




Moisture

Area an d regional managers responsible for thea l loca t ion and c o n t r o l o f surface water have at temptedto forecast the ava i lable mo isture e i th er in the soi l or asfree c rys t a l l i n e w a t e r in the snowpacks , us ing th e

a r i d i t y and an t eceden t prec ip i t a t ion index models . Thei m p l i c a t i o n s are great in te rms of use for ag r i c u l tu ra l en-deavors t ha t depend on soi l /water resources a nd floodforecas t ing fo r l a rge wate r shed s . Th e q u a n t i t y of r u n o f f

produced by a s to rm depends on t he moi s tu re de f i c i en -cy of the basin at the onset of ra in and on charac t e r i s t i c ssuch as ra infal l a m o u n t , i n t e n s i t y , a n d d u r a t i o n . Th ech a rac te r i s t i cs of moi s tu re -de l ive r ing phen omen a canb e d e t e r m i n e d f r o m a n a d e q u a t e n e t w o r k o fmeteo ro lo g ica l gages; but the di rect de terminat ion ofmoi s tu re cond i t i ons t h roughou t a storm is no t feasib le ,an d th e an teceden t p rec ip i t a t i on inde x mode ls c a n o n l y

be used to est ima te re la t ive values for soi l mo isture con-d i t io n s .

M i c r o w a v e i n s t r u m e n t s of the t ype onboard Sky l aba re po ten t i a l l y usefu l fo r de te rmin ing moi s tu re cond i -tions of an area. Those on Sk ylab operated in ac t ive and

passive m o d es and r e sponded to an average value ofsurface or near - su r face mo i s tu re con ten t . Those i n s t ru -ments were not dependent on vis ib le r e f l e c t ance .Mic row ave backsca t te r ( a c t i ve ) and emiss ion (pass ive )are st ron gly depe ndent on the die lect r ic constan t andthe m oisture con tent of soi l, vegetat ion , and snow beingsensed . Th e d ie l ec t r i c cons t an t is a measure of theelectr ic charge on a surface w i t h i n an electric field. Forwater , at microwave frequencies, the die lect r ic constant

is quite large (a s m u c h as 80) , whereas that of dry soil is

t yp i c a l l y less t h a n 5 and t h a t of snow is less t h a n 2.Therefore , the water c on t e n t of soil or snow can great lyaffect the die lec t r ic constant .

A n a l y s i s of the response of t he mic row ave ins t ru -m e n t s (Eagleman e t al . , ref . 3-6)indicates that passiver a d i o m e t e r s , p a r t i c u l a r l y t h e L - B a n d R a d i o m e t e r(SI94) , were most sensi t ive to the pe rcen tage ofmoisture in e i ther the surface layers of the soi l or snowcover . The first step of the an alys is consisted of obtain-ing, b y direct measure ment , de tai led gro und soilmoi s tu re i n fo rmat ion a t t he t ime t he EREP ins t ru -men ts were col lec t ing data. The r esu l t i n g soi l moisturemaps sho wed the percentage of moisture ava i lable in

each 2 .5-cm i nc rem en t to a total dep th of 15 cm. The

correla t ions of the r ad i a t i on rece ived by th e r ad iome te rw i th the moisture content of the var ious layers beneathth e surface were computed fo r each of the 2.5-cm layersto e v a l u a t e th e e f fec t ive dep th f rom w hich th e L -bands igna l or ig ina t ed . In one case , t he an t e nna t empe ra tu re sco r r e la ted w i t h the moisture content in the top 5 cm;

but for the four o the r cases, th e moisture w i t h i n the top2.5 cm pro vide d the best corre lat ion. This resu l t agrees

w i th th e t heore t i ca l ca l cu l a t ions . W hen da t a for the f ive

d i f f e ren t passes were combined , t he co r re l a t i on be -tween th e SI94 rad iome t r i c t empe ra tu re and t he soilmoi s tu re con ten t r emained h igh , w i th a val ue o f —0.96.

The resul ts of the r a d i o m e t e r c o m p o n e n t of theM i c r o w a v e Radiome te r /Sca t t e rome te r and Al t im e te r(S193) were less de f in i t ive t han for the S194 i n s t r u -m e n t . For the same test site and for the s a m e area,when several of the S193 footpr ints were averaged too bta in th e s a m e area covered by the SI94, the corre la-tion o f an tenna t empe ra tu re s w i t h mois tu re con ten tw as -0.988 for the S193 as compared wi th -0.996 fo rth e SI94 . Th e p a r t i c u l a r pass was across Texas on June5 , 1 9 7 3 . W h e n th e S I 9 3 w as used as a sca t t e rome te r , th eresponse to soi l moisture , which is not as good as thatfo r th e radiometers , resul ted in a cor re l a t i on of 0.75.

The analysis of S190A pho tographs and o f image rygenerated f rom the SI92 has show n t ha t , for som eareas, the infra red bands of these sensors can be used toi d e n t i f y s i g n i f i c a n t d i f f e r e n c e s i n so i l moi s tu re .However , di rec t measurements of subsur face so i lmoi s tu re con ten t by op t i ca l and mul t i spec t r a l scanne rdata are di f f icul t because the presence of a vegetativecover tends to shie ld soi l moisture f rom detect ion bythese methods. (See methodology by J . Colwel l ,sec . 6. )

A l t h o u g h opt ica l or mul t i sp ect ral scanners cannotgather qu ant i ta t ive soi l moistu re inform at ion on a prac-tical basis , they can be used very effect ive ly wi thmic rowave da t a to increase th e accuracy of soilm o i s t u r e m e a s u r e m e n t s b y p r o v i d i n g i n f o r m a t i o na b o u t v e g e t a t i o n t y p e a n d d e n s i t y . A n a l y s i s o fmu l t i sp ec t r a l scanner thermal -band data can aid in col -lec t ing and assembl ing surface-temperature informa-t ion .

W hen t he mic rowave an t enna t empe ra tu re s w e reanalyzed for surface emission, which is a func t ion of

th e pe rcen t of soi l mo isture by w e i g h t , i t was conc l uded(Eag leman e t al . , ref. 3-6) that there is a very high cor-

re la t ion be tween an t enna t em pe ra tu re and so i l moi s tu re








fo r values of 0 to 35 perce nt . As the mo isture conten t ofthe soi l increased above ap pro xim ate ly 35 perc ent ,larger dispersions in the data occurred. I t should ben o t e d t h a t t h i s c o r r e l a t i o n i s i n v e r s e ( i .e . , t h emicrowave t empe ra tu re i nc rease s as t he so i l moi s tu repercentage decreases) . A n a l y s i s of the microwave t em-

peratures f rom S193 and S194 inst ruments recordedover snow-covered terrain in the Great Pla ins h ass h o w n t h a t th e re lat ion ship be tween br ightness tem-pe ra tu re s and the wate r con ten t of the su r face of thesnow did not resemble that observed in soi l s . Over thesnow-cove red t e r ra in , t he t emp e ra tu re s we re p ropor -t io n a l to the wate r con ten t of the surface of the s n o w ,and t h e r e was a high degree of cor re l a t i on on l y when

th e free-water content w as between 0 and 2.5 pe rcen t .Th e resul ts of t h i s s tudy , based on l im i t ed mic rowavedata, indicate that i t i s possib le to measure moisturec o n t e n t w i t h a high degree of precision over re la t ive ly

large areas having low quant i t ies of moisture . Bet ter

co r re l a ti ons we re ob t a ined w i th t he S194 ins t r um entthan wi th the S193.

R A N G E

In m o s t of the n o n a g r i c u l t u r a l test sites that weres tud i ed by E R EP inves t iga to r s , r ange lands we re in t e r -mixed wi th forest lands. In fact , th is s a m e i n t e r m i x i n goccurs qu i t e commonl y t h roughou t t he w i ld - l a nd areasof th e w o r l d . Fo r t h i s r eason , t imbe r resources are re-ferred to in th is subsect ion and, converse ly , rangeresources are referred to in the subsect ion on t imberresources.

Range and W i l d - L a n d Classif icat ion Systems

A signif icant con tr ibut io n of the rang eland invest iga-t i ons to the E R E P p r o g ra m was the adap ta t ion of exist -in g vegetat ion c lassi f icat ion sys tems for use wi th Sky l abdata. Classi f icat ion s y s t em s are probab l y th e most im -portant components in the t ransfer of remote-sensingi n f o r m a t i o n , such as t ha t p rov ided by Sky l ab , toresource manager s , p l a n n e r s , and gove rn ment agenc ie s .A m o n g th e various hierarchical c lassi f icat ion sys tems ,

Rober t D. Pfister and Joh n C . C or l is s , "EC OC LA SS—A Methodfor Classifying Ecosys tems" ( repor t on file at Forestry SciencesL abora t o ry , In te rmounta in F ores t an d R a n g e E x p e r i m e nt Stat ion,Missoula , M ont . ) , 1973.

E C O C L A S S 2 i s f r e q u e n t l y used f o r e c o s y s t e mclassification and for improved mul t ip l e -use p l a nn i ng

and m a n a g e m e n t of forest and range resources. TheE C O C L A S S s y s t em l inks vege ta t ion , l and , and aquat i csys t ems wi th t he de sc r ip t ion and c l ass i f i ca t ion o fre la t ive ly pe rmanen t e cosys t ems . The sys t em de f ine s

f ive categories, proceed ing from the most general to themost specif ic , as fol lows.

V. Format ion—The most general c lass of vegeta-t ion , chara c t e r i zed by gene ra l appearance : g rass land ,coniferous forest , deciduous forest , etc. The basis forthis category is c o n t i n e n t a l in scope (i .e. , all the U n i t e dS ta t e s ) a n d i s c o n t r o l l e d b y c o n t i n e n t a l c l i m a t i cdifferences .

IV . Region— Subd ivisions of the fo rma t ion, associ-ated regional ly and the re fo re de t e rmined by subcl i -mate s w i th in con t inen ta l c l imate s : montan e g rassl and ,t empe ra t e mesophy t i c con i fe rous fo re s t , a l p ine grass-l and, e tc .

I I I . Series—A group of vegetat ion systems in theregion ca t egory , w i th a c o m m o n d o m i n a n t c l i m a x

species: ponderosa pine forest , fescue grassland, her-baceous meadow, e tc .

I I . Ha bi tat type — U nits in a ser ies, each w i th

re la t ive ly pure i n t e rna l biot ic an d ab io t ic s t ruc tu re : p on -derosa p i n e / A r i z o n a f e s c u e h a b i t a t t y p e , A r i z o n afe scue /mounta in m uh l y hab i t a t t ype , e t c. These are thee l e m e n t a l un i t s o f t he c l ass i f ica t ion scheme on whi chp r i m a r y management i s based. These uni ts are f re -q u e n t l y re lated to c l imax vegetat ion or to vegetat ionheld in a re la t ive ly stable state of high succession byprope r management .

I . C o m m u n i t y t y p e — A s y s te m t h a t a p p e a rsrela t ively s t ab l e unde r management and may beequ iv a len t t o t he hab i t a t t ype . The b io t i c componen t su su a l ly are d i ss im i l a r , bu t ab io t ic componen t s a reanalogous to habi tat type .

O f the five ecological levels of classification m o s tuseful fo r evalu at ing remote-sensing da ta, hab i tat typerepresents th e level of in fo rm at ion requ i red by vegeta-t ion and land managers for m aki ng resource manage-ment decisions.

Several Skylab invest igators evaluated E R E P datafo r range resources in ve nto ry and an alysis app l icat ion s(Poul ton and W elch, ref. 3-7; Hoffer, ref. 3-8; andAld r ich et al . , ref. 3-9). They fou nd th at S190A color-

inf rared pho tographs we re cons i s t en t l y m o s t useful fo rin te rp r e t in g a wide range of natu ra l veget a t ion types inN e v a d a and Colorad o/N ew Mex ico test s i tes . The




S190A color- infrared film was s ignif icant ly bet ter fo ri den t i fy ing vegeta t ion comp lexes than any o ther f i lmtested, al th oug h S190B color f i l m w as near l y as good fo rother aspects .

A r igorous classification of r ange p l a n t c o m m u n i t i e spe r f o r m e d by the U.S. Forest Service range sc ientis ts

was based on the ECOCLASS sys tem. Identif icat ion attw o levels , three regional and eight ser ies , was at-t em p t ed (Al d r i ch et al . , ref . 3 -9). Photographs from th eS190A m ul t iba nd camera and the S190B ter r a in map-p i n g camera ( June and A u g u s t 1 9 7 3 ) , p h o t o g r a p h s fr o mhigh-a l t i tude a ircraf t ( J u n e and Augus t 1973 ) , and large-sca le pho tographs from a ircraf t were used in the tests.Bo th v isua l and mic rodens i tometer techn iques weretested.

Tra in ing and test sam ple cells were selected for in-t e rpre ta t ion on a restr ic ted random basis . To beselec ted, a specif ic plant community had to occupy anarea at least 500 m squ are. A 10-percent sam ple was

selec ted at random from each plant community c lassfo r field val ida t ion . Over lays of s a m p l e cell locationsand p lan t comm uni ty keys were used to a id in terp re ta -tion. Procedures were also developed to map cu l tu ra lf ea tu res f rom the EREP pho tographs .

Range ecologists , inte rpr et in g S190A and S190Bphotographs, c lassif ied grassland and conifer regionclasses wi th a mean accura cy of 98 percent or greater onboth Skylab and supp or t - a i r c r af t pho tograp hs , r egard -less of date or film type. However, tree series classifica-t ion was inconsistent . Aspen was classified with 80 per -cent accuracy on August color-infrared 1:10 000-scaleaircraft p h o t o g r a p h s , bu t th i s accuracy was not ob ta ined

on EREP pho tographs . Accurac ies fo r con i f erousclassification at the series level were dependent on date,film type , an d scale. Fo r instance, th e Douglas fi r classwas accura te ly c lassi f ied on June co lo r - in f r a red ER EPphotographs but not on aircraf t pho tograp hs . Lodgepo lep ine and ponderosa pine classes were interpreted ac -curate ly on EREP co lo r pho tographs fo r June bu t no ton aircraf t p h o t o g r a p h s . Aircraf t color and color-infrared medium-sca le pho tograph s made in June werebest for interp ret ing the sp ruce /f ir c lass . The greater ac-curacies at smaller scales were probab l y due to the mix-in g of t ree species into homogene ous uni ts wi th a d o m i -nan t species s i gna ture and a lower reso lution .

In the grassland series, shortgrass w as classified w ith95 percent or greater accuracy on both Skylab andaircraf t photographs, regardless of date or f i lm type.W et meadow s were c lassif ied wi th greater th an 90 per -

cen t accuracy on bo th June and Augus t aircraf t p h o t o -graphs, regardless of f i lm type or scale. The classifica-t ion of wet meadows was also acceptable on both colora nd c o l o r- i n f ra r ed E R E P p h o t o g r a p h s t a k en in A u g u s t .M o u n t a i n bunch grass wa s not a ccu rate ly c lassif ied onS190A and S190B ph otog rap hs; but on the Aug ust

aircraf t pho tographs , th e classif icat ion w as accep tab le ,regardless of film type or scale. Topographic slope andaspec t , mounta in shadows , ecotones ( in ter f aces be-tween two ecosystems), season, and class m i x i n gaffected th e classif icat ion of p lan t communi t ies .

E x p e r i m en t a l r esu l ts in the E R EP rangeland s tud ies(A ldr i ch et al . , ref . 3-9) were much affec ted by seasonalt iming of S190A an d S190B photograph acquisi t ion.A l t hough qua nti tat ive resul ts were data depend ent , i twas em pha t ica l ly s ta ted tha t the bes t t ime fo r imagingnatural vegetat ion with color - infrared film is w h e n th evegetat ion types a re a p p r o a c h i n g th e mature g rowthper iod . The E RE P inves t iga t ions ind ica te tha t the peak

growing season (h igh phe nologica l ac t iv i ty ) is thepoorest t ime of year for photographing natural vegeta-tion from space. Mul t ida t e pho tographs , therefo re , p ro-vided th e only means fo r consistent identif icat ion of

some vegetat ion complexes.Mic rodens i tomet r ic po in t sampl ing of region- level

c o n i f e r , d e c i d u o u s ( a s p e n ) , a n d grass land c lassesshowed signif icant dif ferences in mean optical densit iesa t the 9 5 - p e r c e n t - p r o b a b i l i t y l e ve l . H o w e v e r , th edeciduous c lass could be separated f rom the otherc lasses with s ignif icant dif ferences only on color f i lm.Ponderosa pine was the only ser ies- level conifer thatshowed a signif icant dif ference in mean optica l density

from th e other th ree con ifers , regardless of date or filmtype. Spruce/f ir and lodgepole pine were not separableat any date or on any scale or film t y p e . The mean opti-cal density fo r aspen was signif i cantl y dif ferent f romthat for the conifer classes, but the differences were de-pendent on date, scale, and f i lm type. Douglas f ir wasseparable f rom th e other three conifers on both th eJ u n e color - infrared and the August color S190A E R E Pphotographs. Grassland c lassif icat ions at the serieslevel var ied in acce ptab il i ty . How ever , shor tgrass ,mounta in bunchgrass , and wet meadows d id have meanopt i ca l density dif feren ces that were s ignif i cant onAugust S190A color photographs. The optical density

w a s more dependen t o n c o m m u n i t y m i x i n g t h a n on thegrowth stage of the plants at the t ime (season).

B o t h E R E P and aircraft pho tographs were useful fo rmapping the areal extent of conifer and grassland.




These tw o classes were usual ly mapped wi th grea te rthan 90 pe rcent accuracy . The dec iduous c l a ss could notbe map ped w i th acceptab le accuracy a t e i the r the regionor th e series level. Series-level conifer and grasslandcould be m apped wi th accep tab le accuracy only i f c la sscomplexes were formed. Class complexes were pon-

derosa pine and Douglas f i r , lodgepole pine and sprucefir , shor tgrass an d m oun t a i n b unc hg r a s s , a n d w e tm e a d o w .

M a n y dis turbances to na tura l range land vege ta t ioncommuni t i es were recorded . For example , paved andgravel roads, uti l i ty cor r idors cons t ruc ted w i th in the l a s t10 years , larger mining excavat ions , and clus ters ofbu i l d ings could be mapped on S190A and S190B photo-g r a p h i c e n l a r g e m e n t s . H o w e v e r , 1 : 1 0 0 0 0 0- s c a leaircraf t p h o t o g r a p h s were needed to map d i r t roads ,

minor so i l excava t ions , uti l i ty cor r idors more than 10years old, and indiv idua l bui ld ings . Fol i a r cover andp l a n t l i t ter measured on large-scale colo r-infra red

p h o t o g r a p h s of nondiverse gras s l ands were re l a ted toground m e a su r e m e n t s with a cor re l a t ion coef f i c i ent of0.75. T his coefficien t is considered acceptable for rangesurveys . The re l a t ionsh ip for foliar cover of shrubs wasacceptab le only on diverse grass lands .

The use o f E R E P p h o t o g r a p h s fo r vegetat iondel ineat ion was i l lus tra ted by a legend sys tem (Poul tonand W elch , re f . 3-7) in which a mu l t id ig i t a l f ract ion w asused to depic t th e vegetat ive associa t ions (numerator)and l a nd f o r m s ( d e nom i na t o r ) . Th i s system is especiallysui t ed to m ul t i st age remote -sens ing appl i ca t ion s and i sin decimal form fo r c om pu t e r c om pa t i b i l i t y . Th enumera tor i s a three -d ig i t number wi th dec ima l compo-

nents id en t i f y in g th e vegetat ion analog or land use con-di t ions . The de nom i na t o r uses a t h ree -componentdec ima l system fo r l andscape cha rac te r i za t ion . Thec om pone n t s a re macrore l i e f , l andform, and microre l i e f .M acrorel ief refers to the larges t category of class if ica-t ion of major re l i ef change w i th in th e landscape sys tembeing s tudied , wi th the l andform fea ture addres sing thegeomorphological categories as f luvia ls or deserts andthe m icrore l i e f cha rac te rs def in ing the local contours .

A n arid region of the Southwestern United States(fig. 3-7(a)) was class if ied, and a photograph was anno-ta ted (f ig. 3-7(b)) us ing this hier arch ical class if icat ionsy s t e m . The num erical class if iers used for this i l lus tra-

t ion are l is ted in appendix A of reference 3-7.

Evaluat ion of Film fo r Class if icat ion

A l t h o u g h th e legend sys tem is diff icu l t fo r resourcemanagers to use, it can be ap p l ied to l a ndsc a pe b ound -ary de t e r m i na t i on on a Sky la b - q ua l i ty satel l i te photo-graph , as s h o w n in figure 3-8(a) (a n S190A color photo -

graph) and in figure 3-8(b) (a n S190A color - inf rared im -age o f t he U nc om pa hg r e a r ea ) . The ph o t og r a ph s i nfigure 3-9 show sepa ra t ion be tween l andscape types asv i e w e d f r o m l o w - a l t i t u d e a i r c r a f t . H i g h - d e f i n i t i o n

S190B color f i lm was prefe r red fo r m a p p i ng ve ge t a t ionboundar ies because i t has bet ter spat ia l resolut ion (f ig.3 -8 (c ) ) . Ranking benea th S190B color fo r vegetat ionb o u n d a r y de l inea t ion were , in descending order , S190Acolor (f ig. 3-8(a)) , S190A color- infrared (f ig. 3-8 (b)) ,and S192 ( fig . 3 -8(d) ) imag ery . W hen cos t w as con-s ide red , h igh -de f in i t ion S190B color film (fig. 3-8(c))w as considered bes t fo r de l inea t ing vege ta tion bou nd-aries. In most cases, Sky la b s tereoscopic data provided

the best identif icat ion of vegetat ion complexes anddel ineat ion of vege ta t ion boundar ies , par t icu lar ly in

areas where changes in relief were rela ted to changes invegetation types (a common occur rence in wild - lan dvegetat ion c o m m u n i t i e s ) .

FORESTS

Skylab p r ov i de d the first o p p o r t u n i t y fo r fores ters totes t the concept of a manned space l abo ra to ry fo rresource surveys . T hus , remote -sens ing inves t iga t ionsin w h i c h widely separated fores t and wild-land s i tes

were s tudied were conducted to invest igate the ap-pl icabi l i ty of EREP da ta to fores t resources i n v e n t o r yand ana lys i s prob lems .

In t e rp re t a t i on t echniques and ins t ruments used bythe inves t iga t ion t eams to ana lyze E RE P d a ta va r iedfrom o ne appl i ca t ion to a no t he r . Whe n th e E R E Ppho tograph i c produc t s were s tudied , a zoom t rans fe rscope w as used fo r m a p p i n g and dua l - image cor re l a -t i o n s . In f o r e s t- s t r e ss i m pa c t a na l y s i s , a stereo-

microscope w as used to test, m onoc u l a r l y and stereo-scopical ly , a wide range of image magni f i ca t ions . O therforms of manua l photo in te rpre ta t ion inc luded the useof rea r pro j ec t ion v iewers tha t provided image mag-

nif icat ions as large as 29.5 X. On one fores t inv ent ory




task, a scanning stereoscope and a l amp ma gni f i e r wereused fo r c o n v e n t i o n al p h o t o i n t e r p r e t a t i o n .

Two types of dig i ta l method s were used to ana lyzeE R E P pho t op r oduc t s . M i c r ode ns i t om e t e r s we r e usedto scan an d digi t ize S190A and S190B photographs , andtelevis ion scanning sys tems were used to a n a l y z e

digi t ized photographs tha t were d i sp l ayed a t d i f fe ren tgray-scale l eve ls . W i th dig i ta l tapes from th e S192Mu l t i sp ec t r a l Scanner, inves t igators used several typeso f c om pu t e r ha r dw a r e s y s te m s a nd a na l y s i s a l go r i t hm s .

Var ious forest resource app l i ca t ions prob lem s wereaddres sed wi th the a id of ER EP produc t s . Fores tclass if icat ion , a specia l ized area of land use classifica-

tion and a f unc t i on of fores t inventory , was the cor-ners tone act ivi ty of al l fores t ry inves t iga t ions . Th especific tasks related to the data needs of forest resourcemanagers involved de te rmining fores t t imber volume ,s tand vigor (s t ress) , and ownership boundaries .

Classif icat ion

Th e EREP invest igators indicated that , with S190Bcolor photographs , Leve l I forest and nonfores t landareas can be class if ied with 90 to 95 percent accuracy.

(See table 2-1 for Leve l I and Level II class if icat iondefini t ions. ) The accuracy of class ify ing Level II forestand nonfores t classes varied from fair to poor. Hard-wood and pi ne (f ig. 3-10) could be separated w i t h a con-f idence level of 95 percent and an acc uracy of 90 and 70percent , respect ively (ref . 3-9) .

Th e c o m p u t e r m ap s h o w n in figure 3-11 (a ) provides

a visua l compar i son wi th th e S190B photograph ( f ig .3-1 l (b ) ) . A poin t -b y-p oin t compar i son was made be -tween poin t s l ocated on a groun d- t ru th map and the

same point s on the comp ute r m ap. Inves t iga tors foundthat 93 percent of the fores t poin ts were correc t lyclassified as pr in ted on the compute r map. The p inepoints were class if ied with an accuracy of 83 percent .Poin t s fall ing in hardw ood were c l a s s if i ed wi th 74 per-cent accuracy , an d nonfores t points were class if ied w i th

85 percent accu racy . The resul ts of the Ald rich et a l.research (ref. 3-9) revealed that forest area could beclassified and, therefore , s t ra t i f ied on high- resolu t ionS190B pho t og r a phs w i t h an accuracy of a p p r o x i m a t e l y

96 percent . Thus , w i t h S190B photographs , fores t area

c an be m a p p e d and an es t ima te of the l and use areas canb e m a de w i th in l imi t s t h a t can be accompl i shed us ingaer ia l pho t og r a phs .

T h e resul ts o f plant communi ty c l a s s i f i ca t ion t es t si n d i c a t e t ha t both v i sua l an d m i c r ode ns i t om e t r i c t e c h -niques can be used to separate deciduous , coniferous ,

a nd grass land classes to the region level in theE C O C L A S S h i e r a r c h i c a l c l a s s i f i c a t i on s y s t e m . B y

visual ana lys i s t echniques , th e class if icat ion accuracyw as m o r e t han 90 pe rcent on S190B ph otograp hs .How ever , the class if icat ion of deciduous fores t was de-pen den t on th e da te , t he f i lm type , and the s ca l e of thepho t og r a phs . B y m e a n s of microdens i tomet ry ana lys i sof S190A pho t og r a phs , an average accuracy of m o r et h a n 8 0 pe r c e n t w as achieved , a l though th i s accuracy issub jec t to change depen ding on the f i lm typ e and theseason of da ta acqui s i t ion .T h er e was no consis tency inclass ify ing tree categories at the series level by visualp h o t o i n t e r p r e t a t i o n . Conifers were class if ied most ac -

c u r a t e l y (80 pe rcent ) on S190A photographs , whereas ,unde r ce r t a in condi t ions , gras sl and p l ant com mu ni t i e swere class if ied a t accuracies greater than 80 percent .The resu l t s of microdens i tomet r i c t echniques werevar i ab l e and h igh ly dependent on the photograph da te ,film t ype , and scale.

Th e ana lys i s of S192 data (f ig. 3-12) involvedclassi f icat ion of major cover types ( cor responding to

th e Level II l and use classes in table 2-1) and forestcover typ es . The resul ts (Hoffe r , ref . 3-8) indic ated thatthe major cover types could be mapped w i t h a p p r o x -i m a t e l y 8 5 percent accuracy and t ha t th e forest covertypes could be m a ppe d wi th a p p r o x i m a t e l y 71 percent

accuracy . W hen a reas of ma jor cover types ob ta inedfrom ph oto inter pre ta t io n of S190A or S190B imag erywere compared to the a rea summ ary based on t wo c om -pu te r -a ided ana lys i s t echniques , E C H O a nd pe r -po i n tclassi f icat ion, usin g S192 data , a correla t ion coefficientof 0.929 resulted.

Compar i son of the resu l t s ob ta ined wi th S192 da taa n d L a nds a t mul t i s pec t ra l scanner da ta ind ica ted tha tthe im proved spec t ra l re so lu t ion of the S I92 na r row-band da ta enab led a higher class if icat ion accuracy fo r

forest cover types , a l thou gh th e c l a s s i f ica t ion pe r for -m a nc e fo r major cover types was not s ig n i f i c an t l y

dif ferent . The invest igators bel ieve that , had the S192

performance been opt ima l throughout th e miss ion,

A G R I C U L T U R E , R A N G E , A N D F O R E S T R Y 1 0 1



F I G U R E 3 - 7 . — L ' n c o m p a h g r e P l a t e a u a rea of C olorado , ( a ) S I90 A h igh - r es o lu t io n c o lo r - in f r a r ed pho to grap h ( SL3-2 1-00 4 ).(b ) Land use c lass if icat ion us ing the hierarc hica l num ber ing sys tem to depic t landform s and vegeta t ive pat terns .

1 02 S K Y L A B E R E P I N V E S T I G A T I O N SS U M M A R Y



F I G U R E 3 -7 .—Co n c l u ded .








FIGURE 3-8.—Continued.

1 06 S K Y L A B E R E P I N V E S TI G A T IO N S S U M M A R Y



F I G U R E 3 - 8 . —C o n c lu ded .






( a )

P i n e

( b )

Hardwood N onforest W a t er

F I G U R E 3-10.—Pine and h a r d w o o d separation maps of p o r t i o n s of M c D u f f i e C o u n t y , Georgia. M a n y n o n f o res t areas, m os t l y roads or road seg-

ments t h a t a r e b e l o w th e m i n i m u m m a p p i ng s i ze t o separate o n t h e l an d u s e g r o u n d - t r u t h m a p ( f ig . 3-10(a)), a re shown on t h e m a p i n f i g u r e

3-10(b). ( a ) M a p p r o d u c e d f rom d a t a d i g i t i z ed f rom a l and u se m a p . ( b ) M a p p r o d u c e d f rom c l a s s i f i c a t i on o f microdensitometer scans on a nS190B co l o r transparency.

the class if icat ion resul ts would have improved signifi-

can t l y . Also, th e resu l t s indica ted tha t th e increasedspectra l range of the S192 system enables selection of abet ter combinat ion of four wavelength bands for com-puter analys is than is present in the Landsat data .Specific resul ts of the wave length band eva lua t ion s tudyindica ted tha t c l a s s i f i ca t ion pe r formance was not sig-nif icantly improved wh en more than four wave lengthbands w ere used in the comp uter a nalys is . An alys is ofS192 data indicated that the near-infrared part of thespectrum, especially the 1.09- to 1.19-/um wave lengthb a nd , was of particular value fo r vegetation mapping

(Hoffer , ref . 3-8) , with addi t ional wavelength bands inthe visible (0.52 to 0.56 /urn) , nea r infrared (0.78 to 0.88/ u rn ) , and m i dd l e inf rared (1.55 to 1.75 /urn) a lso sh ow nto be of s igni f icant impor tanc e . However , th e c om b i na -tion of four wavelength bands that were of most valuefo r class ifying various cover types varied considerably.

The S192 data collected on A ugus t 5 , 1973 , were pro-cessed to p r oduc e a class if icat ion map of par t of theGra t io t -Saginaw S ta te game a rea in s o u t h - c e n t r a lM i c h i g a n ( f ig . 3 -13) . A p r e l i m i n a r y 1 0 - c a t e g o r yclassification map was prepared for an area consis t ingof diverse vegetation cover types , including hardwood




[a)

F I G U R E 3-11.—Level II classif ica t ion of forest types by com puter analysis , (a) Comp uter map made using diffuse densi t ies converted from o p -

t ica l densi t ies measured on figure 3-ll(b). (b ) S190B pho t o g ra ph t a k en N o v em b er 3 0, 1973 (SL4-90-046).

and con i fer fo re s ts , w e t l ands , b rush l and , and her-baceous vegetat ion. Fie ld checks indicated an ove ra l lp ixe l recogni t ion a ccurac y of 54 percen t , al thoug h ac-cu racy of the m or e poorly c lassi f ied categories rangedfrom 25 to 52 percent . After th e categories w ere l imi ted

to five, the overal l c lassi f icat ion accura cy increasedfrom 54 to 72 pe rcen t . W hen th e output s tat i s t ics werereduced for a square -m i l e g r i d , th e accuracy increased to82 pe rcen t , as the resul t of c o m p e n s a t i n g fo r errors ofomission and commiss ion (Sa t t i nge r et al . , ref. 3-10).

The signal - to-noise rat io of each S192 band presentedmany p rob l ems . Sa t t i nge r et al . (ref. 3-10) identified th e

r e m a i n i n g usable bands in order of preference for sceneclassi f icat ion: (1 ) 0.78 to 0.88 /u,m, (2) 1.55 to 1.75 urn,(3) 0.98 to 1.08 /xm, (4) 0.68 to 0.76 /u.m, (5) 0.52 to 0.56/Am, and (6) 0.62 to 0.67

Type Determinat ion

Densi ty-sl ic ing analyses of S190A an d S190B colorand co l o r - in fra red ph o togra phs , conve r ted to g ray -sca l elevels , have demonstrated the feasibility of using suchdata for d i f fe ren t i a t ing major t imbe r classes ( i nc l ud ing

p ines , hardwoods , mixed , cu t , a nd b r u s h l a n d ) , p r o v i d edsuch ana l yse s we re made at scales of 1:24 000 or l arger(Ba ld r idge et al . , ref. 3-11). D etailed ma ch ine an alyse s,reinforced w i th data f rom knowl edgeab l e field pe rson -ne l , i nd i ca t e tha t suff ic ient spect ral di fferences exist tomake au tomat i c ( compute r i zed) mach ine separa t ion o f

p i n e and hardwo od s t ands poss ib l e . Fur the r dif ferentia-t i on o f mixed hardwood and sof twood types i n wes t ernOh io s tudy s it es , w h ich have smal l , ex t ens ive l y mixedforest stands, was not possib le wi th the use of E R E P

1 1 0 S K Y L A B E R E P I N V E ST IG A T IO N S S U M M A R Y



Sc a le , km

F I G U R E 3-12.—A c o m p a r i s o n of two c l a s s i f i c a t i on systems, "ECHO" and "per-point," u s i n g forested t e r r a i n as a test site. The p e r - p o i n t

classification g i ve s a salt-and-pepper e f f e c t , w h e r e a s t h e ECHO g i ve s a c l a s s i f i c a t i o n s i m i l a r t o t h a t a ch i e ve d by s t a nd a r d p h o t o i n t e r p r e t a t i v e

techniques. T h e v a r i o u s c o v e r types a r e d e s i gna t e d by t h e fo l lowing co l o r codes: w h i t e , s n o w ; l i g h t red, d e c i d uous fo r e s t ; dark red, grasslands;

b l a c k , w a t e r a n d c l o u d s h a d o w s ; a n d b l u e , c o n i f e r o u s fo r e s t , ( a ) P e r -p o i n t c l a s s i f i c a t i o n , (b ) ECHO c l a s s i f i c a t i o n .

photographs. Sample resul ts indicate that densi ty sl ic -in g of E R E P c o l o r and co l o r - in f ra red f i lm may be usedto c lassi fy forest -stand m at ur i ty in Ohio into the fo l low-

in g categories of commerc i a l i n t e re s t : matu re t imbe r ,i n t e r m e d i a t e and po l e t imbe r , seed l ing / sap l ing s t ands ,

b r u s h l a n d , and clear c ut areas.Forest invest igators in Austral ia were able to corre-

late th e occurrence of different forest types wi th var ia-

t ions in color on the S190A color- infrared photographs

( L a m b e r t et al., ref.3-12). They also separa t ed na t iveforest areas into t ree /crown densi ty (crown c losure)

classes and del ineated th e major forest species, event h o u g h th e vegetat ion boundaries were less s h a r p t h a non m i d s u m m e r L a n d s a t - 1 i m a g e r y . Th e b l a c k - a n d -

whi t e pho tographs we re o f l i t t le value for vegetat ionclass if icat ion of forest lands. The invest igators recom-m e n d the use of mid sum mer S190B co l o r - in f ra redp h o t o g r a p h s fo r fo re s t mapp ing .




FIGURE 3-12.—Concluded .

Inventory

The EREP S190A and S190B photograph s w ere suc-

cessfully used to inventory and map a large woodlandarea in Ohio , an accompl i shment demons t r a t ing them i n i m a l r eq u i r em en t fo r supp or t ive g round and aircraft

data (ref.3 -11). Bo th conven t iona l pho to in terp re ta t ionand m achine-assis ted procedu res w ere used effec t ively .

It w as learned that , for the determina t ion of forestcover by counties , Skylab photographs were mo re ac-curate and economica l than conven t iona l su rveys in -v o l v i n g t h e u s e o f a e r i a l p h o t o p l o t t e c h n i q u es .

However , this assessment is not meant to imply thatcost effectiveness w as m a i n t a i n ed in p r o v i d i n g all thei nven to ry and map ping in form at ion genera l ly r equ ir edfor forest surveys.

V o l u m e Determination

Scientists at the Univer s i ty of Californ ia at Berkeley(Colwel l and Benson, ref. 3-13) used SI90A pho to -g raphs as the first stage in a mu ltis tage samp ling designto determ ine the abil i t ies of hum an pho tointerp reters to

1 1 2 S K Y L A B E R E P I N V E ST I GA T IO N S S U M M A R Y



Scale, km

W h i te - Snow

Blue - W a te r

Dark green - Coniferous forest

L i g h t g reen - Deciduous forest

R ed - G r a s s la n d

Brown - Exposed rock and soil

Ye l low - Boundary areas

F I G U R E 3 -13 .—Map o f major cover types obtained b y computer c lass i f i cat ion of S192 d a t a . The two v e r t i c a l l i nes of ye l low dots r epres en t "bad

data."

d i s t i n g u i s h t i m b e r - v o l u m e c l a s se s . Gro s s t i m b e r

v o l u m e was the variable est imated in the s a m p l i n gdesign, based on r a n d o m s a m p l i n g at each of three

stages. Sampl ing un i t s we re r andoml y se l ec t ed at eachstage because i t was not k n o w n how well h u m a n in -t e rp re t e r s cou ld d i f fe ren t i a t e be tween t imbe r and non-

t i m b e r classes on S190A pho tographs in the first stage;therefore , th e classes could b e establ ished quan-t i t a t ive ly , as desi red. A fter al l com bin at io ns of sam pl ingprocedures h ad been te s ted , i t was conc l uded t ha tS190A color- infrared photographs did not have suffi-

c i en t re so l u tion to p rov ide t im be r -vo l um e in fo rm at ionfo r inventory purposes. W h e n th e s a m e ana l ys i s p ro -cedures were appl ied to h ig h - f l i g h t -a i r c r a f t data, the in-

vest igator w as able to es t imate t imbe r vo l ume in thetest area.

Stress Detection

A comp rehens ive eva l ua t ion o f E R E P da t a showed

that mountain pine beet le infestat ions in the Black Hil ls

N a t i o n a l Forest of weste rn Sou th Dako ta cou l d not bede te c t e d o n c o lo r -c o m b in e d m u l t i b a n d , b l a c k - a n d -

whi t e , no rma l co l o r, o r co l o r - in f ra red pho tograp hs f rom

th e S190A mu l t i ba nd camera system ( A l d r i c h et al., ref.3 -9). Al l posi t ive id ent i f ic at io ns were m a d e using S190Bco l o r pho tographs . The infes tat ion s de tected were a l-ways m or e t h a n 26 m in the longest dimension. O n onesite, only infestat ions of m o r e than 50 m could bede tec ted . I t was concluded that poor de tect ion was due

to t i m i n g of the image ry ( June ) and low Sun angle. O p-t imu m v iewing was ach i eved w i th a mic roscop i c v i eweron a good-qua l i t y l ight tab le at a 1:75 000 scale.Stereoscopic vie win g resul ted in fewer errors of com-mission. Because of poor q ua l i ty and misreg i s t r a t i on

between b ands, infes tat ion s could not be detected bycompute r p rocess ing of the S192 data. Fores te r s in O h i oreported th at S190A ph otog rap hs, regardless of filmemul s ion , we re i nadequate to detec t tree stress anddamage co nd i t i ons i n nor theas t e rn Ohio (Bal d r idg e e tal . , ref . 3 -11) .




Image A nno ta t ion an d Over l ays

A precision image annotat ion system w as developedas a cr i t ical par t of a forest invest igat ion in n o r t h e r n

Cal i f o rn ia (Langley a nd Va n Roessel, ref. 3-14). Thet e c h n i q u e extended th e exi s t i ng capab i l i ty of a n n o t a t i n g

th e corners of pr imary sampl e un i t s on aer ial photo-g raphs , L andsa t image ry , a nd t he Landsat mul t i spect ral

scanner data to S190A and S190B pho tographs and togray-scale maps m a d e from S192 data. Image over layswere p roduced by compute r me thods to prov id e v isua l

ident i f icat ion of the sample-uni t corners on each of theimage types . Concur ren t l y , th e coord ina t e s of thepo in t s in the compute r t ape sys t em were de t e rmined .Hence , specif ic sample uni ts were addressable overspect ral bands and t i m e fo r i n t e rp re t a t i on purposes .

The annotat ion system developed is capable of correct-in g for image distor t ions caused by Earth curvature , te r -rain rel ief, and d i s to r t i ons i nhe ren t in the imag ing

sys t em.One of the signif icant resul ts achieved wi th t he an-

notat ion system was the de te rmina t ion t ha t th e root-mean-square e r ro r of point locat ion of S190A imagerywas 100 m and 90 m in the X and Y direct ions, respec-t iv e ly . I t was also l earned that th e potent ial gains insampl ing p rec i s ion a t t r i bu t ab l e to space-der ived imag-ery ranged from 4.9 to 43.3 percent depending on theimage type , i n t e rp re t a t i on m e t h o d , t ime of year , ands a m p l i n g m e thod app l i ed . These results can be com-pared wi th th e 55.1-percent gain achieved by h u m a n in -te rpre tat ion m e t h o d s app l i ed to h igh -a l t i t ude -a i r c raf t

pho tographs .

A signif icant "first" by Hoffer (ref. 3-8) was toana l yze Sky l ab , L andsa t , and t opograph i c da t a all in ac o m m o n fo rmat . Th e Skylab data were correctedgeometr ical ly , and the Landsat data were corrected to acorresponding scale fo r ana l ys is . Topog raph i c m ap data ,which inc l uded aspec t , slope , and elevations, weredigitized and corrected to the appropr i a t e sca l e fo ranalysis wi th th e Sky l ab and Landsat data. This processrequired th e deve l opment of new techniques, inc ludingth e produc t ion of a digi ta l data tape containing 13 SI92

wave l eng th b a nds , 4 Landsa t b a n d s , and 3 bands con-

taining topographic data. These different data sets wereal l geometr ical ly corrected an d registered to a 1:24 000-

scale data base . Digi tal display images in ei ther a graytone or color format and l ine-pr inter outputs weregenera ted f rom topograph i c da t a ; b y th is means, eleva-tion, slope, or aspect could b e indicated with d i f fe ren t

gray tones or colors on the digi ta l d i sp l ay image ry o r

wi th different symbol s on t he l i ne -p r in t e r ou tp u t .

Area De te rmina t ion

R a n d o m and sys t emat i c sa mp l ing de s igns w e retested for measuring forest area proport ions by using a

dig it ized g r o u n d - t r u t h map for one coun ty (Al d r i ch e tal . , ref. 3-9). The var i ance in forest area proport ions w asa l ways l ess wi th t he use o f sys t ema t i c samp l ing , wh ich

stratif ied th e area into forest and nonfore s t ands a m p l e d th e forested area before analy sis . Systema t icsampl ing , w i th the use of digitized S190B optical den-s i ti e s and l i near d i sc r imin an t func t ions fo r pos t sam-p l in g s tra t i f ica t ion, r educed var i ance in forest area pro-

por t i ons at the l ower sampl ing ra t e s . (A t sampl ing frac-

t i ons of more t han 0.0004, th e advantage decreasedr ap id ly . Thi s sampl ing f ract ion represents th e percent -

age of the st rat i f ied forest th at w as sampled on a gr idcoord inate basis. ) In ad di t io n, Hoffer ( ref . 3-8) substan-t iated tha t re l iable areal est imates can be ob tained usingcompute r -a ided ana l yse s of satell i te data even in areasof rugged , mou nta inous t e r r a in .

Recrea t iona l Potent ia l

Sattinger et al. (ref. 3-10) provided a qual i t a t i ve

evaluat ion of both S190A an d S190B photographs andconcluded tha t S190A h as l imi ted app l icat ion for recrea-

t ional land use ana l ys i s , but that S190B, with a resolu-

t ion appro ach ing tha t ob t a inab l e f rom h igh -a l t i t udeaircraf t , is useful fo r ma ny l and ana l ys i s app l i ca t ions .Th e invest igators have stated that S190B photographs

con ta in suff ic ient detai l to map Level I and Level IIcategories of l and use and l and cove r . App l i ca t ions in -cluded mapping exist ing recreat ional faci l i t ies , ident ify-

in g open spaces that might be sui table as recreat ional

l and , and site p l a n n i n g of geograph i ca l l y ex t ens iveareas, such as r iver basins.

Tempora l Variat ions

Th e evaluat ion of temporal S190A an d S190B p hoto-g raphs showed th e impor t ance of season in re lat ion toth e ana l ys i s of mult ispect ral scanner data (Hoffer , ref .3-8). Th e pho to in t e rp re t a t i on re su l t s i nd i ca t ed t ha t ,

1 1 4 S K Y L A B E R E P I N V E S T I G A T I O N S S U M M A R Y



because of di fferences in vegetat ive condi t ion, theS kylab 2 data obtaine d in June over Colorado were be t -ter for vege ta t ion map p in g t ha n those ob t a ined in

A u g u s t .Lan g ley and Van Roessel 's results (ref. 3-14) con-

f i rmed t ha t seasonal var i a t i ons , as recorded on fi lm,

were s ign i f i ca n t fo r fo re s t i n t e rp re t a t i ons . In t h e i r s t u d yconduc ted in C a l i fo rn ia , t he S190A pho tographs ob -t a in ed dur ing Sky l ab 3 (Sep tember ) y i e l ded h ighe r i n -

t e rp re t a t i on accuracy t han t hose ob t a ined in June ;how eve r , S190A co l o r - in f ra red compos i te s f rom bo tht ime per iods y ie lded the highest resul ts of al l S190Aproduc t s ana l yzed . N o S190B pho tograph s w e re ava i l a -ble for t h i s s tudy ; t he re fo re , no S190B temporal com-

binat ions were possib le .A l t h o u g h m a p p i n g of all the forest and rangeland

(6070 x 109 m 2 (1 . 5 X 109 acres)) in the United Statesat frequent intervals i s desi rable , l imi tat ions in com-p u t e r s and computer s torage make detai led and re -

peated inventor ies unfeasib le at the present t ime. In -stead, it is much more reasonable to t h i n k of s a m p l i n g

a p p l i c a t i o n s . Fo r e x a m p l e , i t was d e m o n s t r a t e d( A l d r i c h et al . , ref . 3 -9) that a systemat ic sample gr idcan be overlaid on digi t ized l and use map data by com-p u t e r to est imate forest and nonforest land in an ent i recounty . (The var iance w as alwa ys lower than thatre su l t ing f rom s imp l e r andom sampl ing . ) Us ing Sky l a bcolor film to classify forest and nonforest land in an en-

t i re coun ty resul ted in an acc uracy of 80 percent forforest land, wi th a 30-percent commission error . Types

of forest and other land covers m a y b e est imated b ysampl ing digi t ized data f rom fu tu re sate l l i te coverage if

color- infrared film is m a d e avai lable and if a classifica-tion system based on the exis t ing land cover rath er than

on in tended use is designed.The pr imary advan tage of Skylab S190A and S190B

p h o t o g r a p h s in forest resource surveys is the broad area

coverage w i t h i n a single f rame. In the 4-county exper i -m e n t , 18 3 aer ial ph otograp hs (1:20000) were requiredto cover an est imated 80 pe rcen t of the total area. Thisw as s ing le p ho tog raph i c cove rage wi tho u t th e a d v a n -tage of stereoscopic over lap. A single S190B photo-g r a p h , h o w e v e r , wil l cover these four count ies a nd f rom

two to four add i t ional count ies as wel l . Com ple te coun-ty coverage offers be t ter dist r i but ion of photo grap h

samples and reduces data handl ing and pho toacqu i s i -t ion costs , on the assumpt ion t ha t on l y p r i n t i n g andprocessing costs a re i nvo l ved .

If all other survey costs are considered equal , th e

costs of Level I and Level II land use and forests tra t i f ica t ion would be 49 percent lower using S190Bphotographs t han on conven t iona l 1 : 20 000-scale aer ialb l a c k - a n d - w h i t e p h o t o g r a p h s . Th e major d i f f e rence be-

tween the two method s i s the cost of the pho togra ph s.Because of the smal l scale and the use of normal color

f i l m , more t ime was r equ i red to make in t e rp re t a t i vedecisions on S190B photographs. However , i f h igh-re so l u t ion co l o r - in f ra red pho tog raphs we re ava i l ab l e ona regula r , rec urr in g basis , the ad vantages o f cu rre nt in-f o rmat io n would far outweigh the disadvantage of anyad d i t io n a l i n t e r p r e t a t i o n t im e .

S U M M A R Y

Several scient if ic invest igat ions in the disc ipl ines ofa gr i cu l tu re , r ange managem ent , and fo re s t ry ana l yzed

th e E R E P d a t a to con t r ive t e chn iques a nd proceduresfo r extract ing th e r equ i red r e source i n fo rmat ion . Thei m a g e r y w a s a c q u i r e d i n a m u l t i s p e c t r a l f o r m a t ,ana l yzed by v i sua l i n t e rp re t a t i on , and d ig i t i zed fo r com-

pu te r ana l ys i s . Th e narrow-band spect ral data as ac-quired by the S192 inst rument were analyzed by com-puter processing to ident i fy th e op t imum spec t ra l bandsand c o m b i n a t i o n s of these b a n d s t ha t wou l d p rov idem a x i m u m a m o u n t s of resource i n f o r m a t i o n a t am i n i m u m c o s t . M i c r o w a v e d a t a r e c o r d e d in ane l ec t ron i c fo rmat p rov ided an ins igh t i n to t he mapp ing

and moni to r ing o f a va i l a b le mois tu re fo r na tu ra lr e source consumpt ion . Eval ua t ions of the ut i l i ty andr e commendat ion of data fo rmat s and required observa-t ion frequency fo r discre te resource moni to r ing ormeasurement s us ing ERE P-q ual i t y da t a we re alsom a d e .

Fo r i den t i fy ing and measur ing field crops (i .e. , cropsgrown in larger tracts (32 to 65 hm

2(80 to 160 acres) )

and in the categories of cereal or large-area crops, asdif ferentia ted from vegetables) , i t was found t ha t th emul t i spec t r a l pho tographs we re appropr i a t e fo r i nven -to ry in g w i t h i n an accuracy r ange of 82 to 98 percent . Toident ify large-area crops using single-date data, i t wasde t e rmined t ha t th e data would have to be acqu i red p re -cisely when th e c rops we re matu r ing ; bu t when t em-pora l or mul t i da t e da t a we re used , th e acquisi t ion t imewa s no t a s c r i t i c a l a n d d a t a c o u l d b e a c q u i r e d

t h r o u g h o u t t h e d e v e l o p m e n t p h a s e a n d b e f o r em a t u r i t y . W h e n data acquired from these s a m e types of




crops were analyzed, th e resul ts were equal ly as good

with ei ther digit ized photographs or elec tronical lyrecorded S192 data. Large-area crops ge neral ly follow auni form planting and harvest ing calendar for a givengeographical region and meteorological environmentand are compat ib le wi th th e ident i f iable types of re-

quired data and the ap prop r iate t imes for acquisi t ion ofth e data.

W hen in tens ive ly cu l t iva ted crops (vegetables) werestudied, i t was concluded that the t i min g of data acquisi-t ion was extremely cr i t ical and that data should be ac-quired at discrete stages of m atur i ty . A cqu is i t ion ofthese temporal d ata consti tuted an addit iona l problembecause vegetable production areas f r equen t ly have onetype of crop in two adjacent fields at different stages ofmatur i ty and thus require m o r e f requent observationintervals .

Generally, field sizes smaller than 2 hm2

(5 acres)were diff icul t to discr iminate with the resolution of the

E R E P sensors . As the f ie ld sizes increased, th e iden-t ification and areal measurement accuracies also in-creased.

W ith use of the full range of the mult ispectral photo-graphic system, four bands (green, red, and two in-frared) were the most usefu l fo r inven to ry in g andmonitor ing vegetat ive resources, al though only twobands were analyzed fo r vegetat ive resources. Th enatural color and color - infrared bands were th e mostfrequent ly used. Analysis of the narrow 13-bandelectronic data indicated that a yellow band a nd 3 in-frared bands p rov ided th e greatest a m o u n t of in fo rma-t ion .

Th e pho tograp h ic sys tem, th e 13-band S192, and themicrowave systems were used to map various soilparameter s . The areal extent of soil units w as mappedusing th e color and co lo r - in f r a red pho tographs . W h e nthe soil was visible , color was the ind ica tor of soil units;and when the soil suppor ted vegetat ion, the vegetat ion

boundar ies were considered synonymous with soilunits and used for mapping.

Soil sal ini ty was mapped over a l imite d test s i te byana l yz ing SI92 data. The indic ator was the qual i ty ofvegetat ion as correlated w i t h th e elec trical con duc tivi tyof the soil . This technique is p r o m i s i n g fo r saline soilm a p p i n g bu t will require addit ional s tudy fo r ref ine-men t .

The availab le soil moisture in the top 15 cm for p lan tc o n s u m p t i o n w as m a p p ed f r o m S 1 9 3 and S194mic rowave data. Correlat ions of soil moisture between0 and 35 percen t by we ight were very good; but forl a r g e r p e r c en t a g es o f m o i s t u r e , t h e i n s t r u m en t

responses were saturated. Similar resul ts w ere ob tainedwhen the water equivalent of snow cover ing the GreatPlains area was mapped.

W h e n m a p p i n g wild - lan d resources, which inc luderangeland and forest environments , accuracies forLevel I and Level II were 90 to 95 percent and 70 to 90percen t , r espec t ive ly . Conven t iona l pho to in te rp re ta t iontechniques were used, with the preference of f ilm typesbeing high-def ini t ion color f rom th e S190B because ofit s better spatial resolution, fol lowed by S190A colorand S190A color infrared, respectively . Level I I land useclasses, as identif ied in table 2-1, were id en tifie d byanalysis of S192 data at an accuracy of 85 percent .

1 1 6 S K Y L A B E R E P I N V E S TI G A TI O N S S U M M A R Y



Invest igators achieved l imi ted success in detect inginsect damage by anal ys i s of ER EP da t a . They ind i -cated that the residual effect , or change in vegetat ivestate, w a s suff ic ient ly l imi ted to prevent de tect ion wi thth e r e so l u tion -ce l l c apa b i l i t y of the sensors and t h a t th edata were no t acqu i red at the op t imum b io l og i ca l

pe r iods of insect activities. In the case of the pine barkbeet le damage to conifer forests and meal ybu g in fe s ta -tion on c i t rus , th e period of m a x i m u m b i o l o g i c a l ac -t i v i t y produces th e maximum v i sua l change in thecharac t e r of the vegetat ion. The general conclusion ofm o s t of the i nves t iga to r s w as t h a t th e E R E P - q u a l i t ydata are acceptable for Level I and II mo ni tor ing but re -quire acquisi t ion at op t im um t imes w i thi n the develop-mental s tages of the vegetat ion and shou l d be ana l yzedby personnel thoroughly famil iar wi th the resource in

ques t ion .

R E F E R E N C E S

3-1. Hart, W. G. ; Ingle , S. J.; and D av is , M. R. : A Study of the

Ear ly Detec t ion of Insec t Infes ta t io ns and D ens i ty Dis tr ibu-

t ion of Host P lan t s . NASA CR-144483 , 1975.

3-2. D e Men do n c a , F. ; M a c h a d o , J. B.; et al. : Collection of R e le -

vant Resul ts Obtained W ith th e Sk y lab I mag es . NAS A

CR-147502, 1975.

3 -3. Colwel l , Rober t N. ; Benson, A nd rew S. ; e t a l . : Ag r icul ture

I n te r p r e t a t io n Tec hn iqu e D ev e lo pmen t . NASA C R - 144486 ,

1975.

3- 4

3-5.

3 -6 .

3 - 7 .

3 - 8 .

3-9.

3-10.

3-11.

3-12.

3-13.

3-14.

B a n n e r t , D .: Hydrological Inves t igat ions in the P a m p a of

Ar g en t in a . NASA C R - 144488 , 1975 .

W i e g a n d , C r a i g

CR-144403, 1975.

L . : So i l S a l i n i t y D e t e c t i o n . N A S A

E a g l e m a n , J . R. ; L i n , W.; e t al . : Detec t ion of Soil Mois ture

an d Sn o w C ha r ac te r i s t i c s From Sk y lab . NA SA C R - 144485 ,

1975.

P o u l to n , C . E . ; an d W e lc h , R . I . : P l an f o r t he Un i f o r m M ap -

p i ng o f Ea r th R es o u r c es a n d E n v i r o n m e n t a l C o m p l e x e s

From Skylab Imagery . N AS A CR-144484, 1975.

Hoffer , R o g er M. : C o m pu te r - Aid ed An a ly s i s o f Sk y l ab

Mul t i sp e c t r a l Sc an n e r D a ta in Mo u n ta in o u s Te r r a in f o r

Lan d U s e , Fo res t r y , W a te r Reso u rce , an d G eo lo g ic A pp l i c a -

t ions. NA SA C R - 147473, 1975 .

A l d r i c h , R o b er t C . ; D an a , R o b e r t W . ; e t a l . : Ev a lu a t io n o f

Skylab ( E R E P ) D a t a f o r Forest an d R an g e l an d Su r v ey s .

NASA CR-147440, 1975.

Sa t t in g e r , I. J. ; Sado ws k i , F. G.; and R o l l e r , N. E. G. :

A n a l y s i s o f R ec r ea t io n a l Lan d Us in g Sk y lab D a ta . N AS A

CR-144471, 1973.

B a l d r i d ge , Paul E. ; Go es l ing , P . H. ; e t a l . : Uti l iz ing Skylab

Data in On-Going R esources M anagem ent Program s in the

State of Ohio. NASA CR-134938, 1975.

Lamber t , B. P . ; Benson, C. J . ; e t a l . : A Study of the Useful -

ness o f Sk y lab ER EP D a ta f o r Ea r th Reso u rces Studies in

Au s t r a l i a . NA SA C R - 144493 , 1975 .

Colwel l , Rober t N.; and Ben s o n , An dr ew S .: Sk y lab D a ta as

an Aid to R es o u r c e Man ag emen t in No r the r n C a l i f o r n ia .

NASA CR-144487, 1975.

Lan g ley , Phi l ip G.; and Van Roessel, Jan: Th e Us ef u ln es s of

Sk y lab / ER EP S190 and S192 Imagery in Mu l t i s t ag e ForestSu r v ey s . NA SA C R - 14743 9 , 1976.






Geology and HydrologyR I C H A R D A. HoppiN.at

D U W A Y N E M . A N D E R S O N ,bf

ROBERTK. S T E W A R T S DA vioL. A M S B U R Y ?

V O N R . FRlERSON,d A . V IC T OR M A Z A D E , d

A N D M A R T I N L . M I L L E RC

TE A P P L I C A T I O N OF R E M O T E S E N S I N G to geologicalstudies began in the ear ly 1920's throu gh the use of

visual ana l ys i s of ae r i a l pho tographs , and the i r use ad-vanced rap id l y after W o r l d W ar I I for regional geologi-cal map ping and fo r pe t ro l eum and mine ra l exp l o ra t ion .The use of photogeology reached it s peak in the U n i t e dStates by the m i d d l e 1950's. The d i s t r i b u t i o n ofh a n d h e l d - c a m e r a p h o t o g r a p h s t a k e n d u r i n g th e G e m i n iProgram in the mid-1960's and of data f rom th e Apol l o ,Land sat , and S kylab Programs in late 1960 and the ear ly1970's increased th e in terest in the use of space remote-sensing surveys for geological and hydrological s tudies.

Several types of geological and hydrological s tudieswere conducted b y approximate l y one - th i rd of theS kylab invest igators . Geologic studies included regional

ma pp ing o f s t ruc tu re and l i t ho l ogy ; mine ra l , p e t ro l eum,and geo the rmal exp l o ra t ion ; mapp ing o f vo l can i cp h e n o m e n a ; m a p p i n g o f fau l t systems for locat ion ofac t ive ear thquak e zones ; and m a p p i n g of f r ac tu re zonesin a coal mining area fo r mine safe ty purposes . W ate rresource studies included analysis of such features ass t r eamf l ow, eff luent discharge , r iver s tage , f looding,snow accu mul a t ion and a b l a t i on , e s tuar ine c i r cu l a t i on ,sed imenta t ion , s t r eam e ros ion , and shore l ine r e t r ea t .

aU n i v e rs i t y o f Iowa.

''U.S. A r m y Corps of Engineers .C

N A S A L y n d o n B . Johns on Spa ce Cen te r .dL o c k h e e d Elect ronics Company, I n c .

P r i n c i p a l Invest igator .

Hydrological s tudies were di rected to gene ra t ion ofmod e l s o f g round wa te r mov ement , de t ec t ion o ft r apped g round wate r a l ong fau l t s , and s tud i e s o f t her e l a t i o n s h i p of g r o u n d w a t e r to p h o t o l i n e a rs . A l t h o u g ht h e E a r t h R e s o ur c es E x p e r i m e n t P a c k a g e ( E R E P ) in -vest igators s tudied a wide var ie ty of te rrain andgeographic areas, domest ic invest igat ions were con-centrated in the Great Plains area and the C e n t r a l andW estern Uni ted States. Three invest igators analyzed

dat a of the A p p a l a c h i a n M o u n t a i n s of the Eas te rnUni ted States. Invest igat ions were also conducted inCent ra l and South Am er i ca , Europ e , A fr ica , andAu s t r a l ia .

Resul ts of the Sky l ab E R E P studies show that th e

m o s t prac t ical and useful space sensor for geologicalstudies is a h igh - re so l u t ion camera . The pho tographsfrom th e Earth Terrain Camera (S190B) wi l l p r o b a b l ycon t inue to be the data mos t in d e m a n d b y geologists.Th e main advan tages of the E R E P c a m e r a s y s te m s a resynop t i c v i ew, s t e reoscopy , and resolut ion. For f ie ldgeo log i st s , the synop t i c v i ew i s a par t i cu l a r l y impo r t an ta id in unde r s t and ing and in t e rp re t ing t he r eg iona lgeology of an area because i t provides an expanded op-p o r t u n i t y to look at the total area of interest . Space data

in t he fo rmat o f co l o r o r co l o r - i n f ra red pho tographsenab l e th e geologist to map and extend t r ends fo r great

distances and to pe rce ive anomal ous areas t h a t m a y b ein d ica to r s of subsur face s t ruc tu re s capab l e of t r a p p i n goi l or gas or o f con ta in ing p rospec t ive mine ra l depos it s .

Frac tu re sys t ems and rock al te rat ion zones are p r o b a b l y

t he two most use fu l i nd i ca to r s of m i n e r a l i z a t i o n .These

119





F IGU RE 4 - 1 . —Are a s ou t h w e s t o f M oab , U t ah , s h ow i ng th e junc t i on o f th e Co lo rad o and Gre e n Ri v e r s , ( a ) S 19 0B p h o t ograp h (SL2-81-016).

(b ) U.S. Geo logical Surv ey map (1 :250 000 scale ) based on aer ia l photogra phs and f ie ld wo rk ( ref . 4 -3) . (c) Detai led geological map (1 :62 500

sca l e ) p re p are d f rom S I9 0 B p h o t ograp h s by L e e (ref . 4 -2) .

G E O L O G Y A N D H Y D R O L O G Y 1 2 1



FIGURE 4-1.—Cont inued.

In the Canyonlands Nat iona l Park in U t a h , Lee et al.(ref. 4 -2 ) used an ER EP ph otog raph ( f ig . 4 -1 (a ) ) to mapal l the sedim entary rock forma tions ranging in age fromPennsy lvan ian to Quaternary tha t appear on thepublished U.S. Geological Survey 1:250 000-scale m apof this region (fig. 4- l (b) ) . A t th is scale, EREP photo-graphs made possible some subdivision of fo rmat ions

in to members as well as the m a p p i n g of s t r a t ig raph icpinchouts , inter tonguing sedimentary rocks, and lateralfacies changes. The pho tographs and the topographicmaps were used to es t imate th e th ickness of majorstrat igraphic units . M ost m ajor geological s tructureswere recognized, and the dip of beds w as est imatedwi t h i n 2° of field measurem ents . Du r ing this invest iga-

122 SK Y L A B E R E P IN V E S T I GA T I O N S S U M M A R Y





1,1

F I G U R E 4-2.—San R af ae l Swel l area , Ut ah, (a) S190A color photograp h (SL2-10-010). (b) Photogeological map deriv ed from stereoscopic ex-aminat ion of Skylab S190A and S190B photographs .




a

E

( b )

| Q A L . |

Al luvium deposits

| T P C

Paleocene continentald e p o s i t s

J K M U C

M e s a Verde Group

I * M \ KuFE-Ferron member

M arcos Shale

S a n R a f a e l GroupI - - 1 M orrison Formation

I *JSR

I Summerville Formation

Entrada Sandstone

Glen Canyon Group

-i N avajo Sandstone

•^G

I Kayenta Formation

W ingate Sandstone

Chinle Formation unconformity

Moenkopi F ormation

K a i b a b Limestone a n d Coconino

S a n d s t o n e o f Utah

^*20

S c a l e , k m

0 Horizontal bedding

J - D ip 0° to 5°

- " - " - Dip 6°to 45°-A- Dip 45°o vertical

yf Fault

- -f Fault, inferred

— Lineament

-4*- Anticline

-J - Syncline~ Geological contact,

d a s h e d whereindefinite

G E O L O G Y A N D H Y D R O L O G Y 1 25





Clouds

W i nd R i v e r Basin

0 10 iS c a l e , k m /

.

Tu -Tertiary, undifferentiated

T f - Fort Union ( P a l e o c e n e )

Ju -Ku -Jurassic-Cretaceous, undifferentiated

ftc -Tr iass ic , C r t u g w a t e r Formation

P p - P ermian, P hosphoria F ormation

€ - P p - Cambrian to Permian units

P £ - Precambrian

High-angle faultsLinears

{ •• Anticline-j Syncline

} M onocline

D ip direction

(b )

F I G U R E 4-3.—Concluded.

GEOLOGY AND HYDROLOGY 127





FIGURE 4-4.—Continued. (Symbols ar e explained on the following page.)




Photogeolog ic M ap Units an d

Approx ima te G eo log ic M ap Un i t E q u i v a le n ts

Q al

Alluvium

QP 9

P ed iment g rave ls

M esa Verde Fo rmat ion

at base; Lance

Fo rmat ion at top

Basal contact of

Shannon Sandstone;

member of Cody Shale

M ost ly Cody Shale

| Kf |

M ost ly F ron tie r

Fo rmat ion

Si l i ceous shales of

th e M owry Fo rmat ion

Black sha les of the

Thermopolis and

M owry Fo rmat ions

[ Kcv |

Cleverly Fo r ma t i o n

.™ I Inc ludes P ermian

•5 \ G oose Egg Format ion,

E I and T r iass ic Chugwater

£ \ F o rmat ion most ly

M ostly Tensleep

Sandstone

Mostly Mississippian

M ad ison L imestone;

includes some

B i g h o r n Dolomite

of O rdov ic ian ag e

£ / Undivided

1

F I G U R E 4 -4 .—C onc luded .

m a r k e r bed for interpret ing th e s tructural features .High-resolu t ion b l ack-and-whi te photographs of the"Horn" area (ref. 4-5) in the Bighorn Mounta inspor t ray th e s tructural set t ing of the region, which a idsin planning deta i led geologic analys is .

Th e Alice Springs area in the arid centra l part ofAustra l ia was mapped by Lambert e t a l . ( ref . 4-6) fromEREP photographs , and the results were verif ied b yf ield studies. These ana lyses showed tha t th e s tr ike o foutc ropping uni t s w as mapp ed accura te ly , t ha t know n

folds were ident i f i ed , and that areas of m e t a m o r p h i cand younger sedimentary rocks and Tert iary surficial

deposits were del ineated. Circular features detected on

the photograph s were found b y f ie ld s tudies to be a r ingdike, a grani te intrus ive, and a landsl ide.

In contras t to the ap pl ic at ion of color pho tograp hs inphotogeologic analys is of semiarid regions , color-inf rared an d b l a c k - a nd -wh i t e i n fr a r e d pho t og r a phs aremos t useful in he avi ly vegetated regions . S truc ture can

be revea led by l andform s as in the A ppa lach ian Moun-ta ins , where long, vegetated r idges are caused by resis-t a n t sandstones that resul ted from th e folding t h a t oc -cur red in this region. In the Black Hil ls of South Dakota ,th e P r e c a m b r i a n m e t a m or ph i c a n d gra n i t i c r oc k s a n d

th e Paleozoic sedimentary sequences are tree coveredand appea r da rk in the inf ra red photographs (figs.

4-5(a) and 4-5(b)). The color-infrared photograph (f ig.4-5(b)) show s the d is t r ib ut io n of the Triass ic red bedthat out l ines the regional extent of the Black Hills

upl i f t . Th e l i ne a m e n t m a p (f ig. 4-5(c)) d erived from th ephotographs suggests a varia t ion in pat tern in thePaleozoic and Precambrian rocks that is an a id in

del ineat ing t he contac t .In the areas of l imited geological info rm atio n, suchas Cent ra l A mer ica , Skylab pho tographs have a ided inth e compi l a t ion of new i n f o r m a t i on t ha t c an form th ebasis fo r fur the r spec ia l i zed mapping . Good e x a m p l e sare in Ce ntra l Am erica (ref . 4-7) and nor theas te rn Spa in(ref . 4-8) . The usefulness of the photographs from

spacecraft sensors varies with regional set t ing and en-v i ronmenta l condi t ions a t t he site; table 4-1 provid es acomp ar i son of the inform at ion content of the da ta ac -quired over the Great Pla ins area , which has subduedtopo grap hy, heavy soi l and vegetat ion cover, and a largeamount of manmade d i s turbance ( re f . 4 -9) .

L inea r and l ineament maps a re comm on produc t s ofphotographic analys is . A l i ne a m e n t is defined as anyunid imens iona l s t ra ight or cont inuous ly curved com-b ina t ion of pictu re elements th at appears on pho to-graphs or images and that is thought to have geologicsignificance (ref. 4-2). Straight or l inear features onphotographs have many poss ible causes . They may ap-pear as alined sags and depressions, ridge gaps, tonaldifferences, al ined springs , vegetat ional trends andtypes , s t ra ight drainage segments, r idges , texturaldifferences, and cul tural features . Many l inears a refau l ts or fracture t races , bu t unequivoca l ident i f i ca t ionof a l l l inears canno t be made f rom p hotograph s ; some-t imes , iden t if icat ion cann ot even b e mad e after f ie ld

check ing .Olson (ref . 4-10) found many topographic l inears in

South Carol ina and no r t he r n Georgia to be paral le l to




FIGUR E 4-5.—Black Hil ls , South Dakota , (a ) Black-and-w hite infrared photograph (SL2-08-113). (b) Color- infrared p hotograph wi t hPaleozoic rock outlined (SL2-09-121). (c) Lineament map of lower portion of photographs.




FI G UR E 4 - 5 . —C o n t in u ed .

zones of crushed rocks or to coincide with previouslymapped regional f rac ture trends. Because l inear pat-t e rns are of ten paral lel to f rac ture and/or fau l t pat ternsas determined on the ground, l inear diagrams are com-monly considered to be reasonable approximations offracture t rends. In the Black Hills of South Dakota,Hoppin et al. (ref. 4-4) noted a s t rong nor th -nor thwes t

l inear trend in the Precambrian core that paral lels awidesp read, c losely spaced f rac ture system com monthroughout the region.

A majo r goal of the geology studies was to determineth e scale, th e resolution, and the spectral bands bestsuited for interp retat ion . M any investigators comparedth e n u m b er and length of l inears observed on Landsa t

1 3 2 S K Y L A B E R E P I N V E S TI GA T I O N S S U M M A R Y



< ^ O S \ M V ' '


imagery, Skylab S190A and S190B photographs, and

aircraft pho tographs . In general , more l inears werefound on S kylab pho tographs than on Landsat images.Longer l inears were noted on L andsat images andshor ter ones on aircraf t p h o t o g r a p h s . Th e a c t u a l n u m -ber observed can be a function of the season of the yearin w h i c h th e imagery is obtained. Cassinis et al . (ref.

4-11) noted that linear detection on the Skylab photo-graphs acquired over Italy in September 1973 was not as

good as on the L andsat imag ery , because of the low con-trast caused by unifo rm ref lec tance from vegetat ion.From geologic s tudy of western Colorado , Lee et a l .(ref. 4-2) showed that linears are selectively enhanced

as a func t ion of Sun eleva t ion , S un a z i m u t h , and l inear






T A B L E 4-1.—Concluded

Attribute*

Stereoscopic

coverage;

slereovision

0 10 2.5

0 to 2.5

0 to 2.5

0 to 2.5

0 to 2.5

0 to 2.5

O t o 3

'

u

( 1

0

0

0

1

0

0

0

0

1.5

1.5

1 -

1.5

Metric

(planimetric)

capability

•

3

2.5

2. 5

3

3

1

.

I

2

.

;

2

2

2

2

2

2

2

3.5

3.5

3.5

3.5

Water-body Cloud/snow Water

detail

1 to 2.5 2 0.5

2 to 3 1 0

1 to 3.5 1 0

1 to 3.5 1 0

1 to 3 1 0

1 . 5 2

1 to 3 2 1

Oto 1 0

0 to 1 .5

0 to 1 .5

0 to 1 .5

Ot o 1 0

Oto 1.5 2

Oto 1.5 2

Oto 1.5 2

0 to 1 2.5

1 to 2 3

0 to1 3 -

1 0 —

0.5 .5 2

1 to 2 1 0

2 to 3.5 1

2 to 3.5 1

Vegetation Agricultural

land use detail

2 to 3 3 to 3.5

3.5 2 to 3

0 . 5 t o 2 1

0.5 to 2 0.5

2.5 3

1 1.5 to 3

2 to 3 3.5 to 4

0.5

0.5

0.5

0.5

0 to 0.5

0.5 to 1

0.5

0.5

0 to 0.5

0

0

0

0.5 0.5

2.5 1 to 3

2 1 to 2.5

2 I t o 3

Topographic

(landform and

stream pattern)detail

3 to 3.5

2 to 3

0.5 to 1

0.5

3 to 3.5

1 to 2.5

3.5 to 4

O t o l

1 to 2

1 to 2

0.5 to 2

O t o 1

1 to 2

1 t o 2

1 to 2

1 to 2

O t o 1

0 to 0.5

0

0.5

1 to 2. 5

1 t o 2

1 to 2.5

Geological

linear

detectability

2 to 3

2 to 3

0.5 to 1.5

0.5 to 1

2.5

0.5 to 1

2.5 to 3.5

0.5

0.5 to 2

0.5 to 2

0.5 to 2

1

2.5

1 to 2

1 to 2

1 to 2

0 to 0.5

0

0

0.5 to 1.5

2 to 3.5

1 .5 to 3

1 .5 to 3

A \-eragt'

value

2.6

2. 4

1.5

1.3

2.3

:

2.7

•

1

1

1

•1.4

1.3

1. 2

1.2

.9

.8

.6

1 .6

2.3

.'4

\A

a N u m e r i c a l r a t i ng system: 0 = ver y poor, 1 = poor , 2 = f a i r , 3 = good, and 4 = excellent.




or i en t a t i on . Frac tu re s as short as 1 km can be recog-nized o n S190B pho tographs a n d jo i n t spac ing le ss t han

200 m can be resolved.

L a m b e r t et al. (ref. 4-6) c o m p a r e d the n u m b e r of

fau l ts shown on a 1:250 000-scale geological map andthe number of faul ts detected by i n t e rp re t a t i on of

sa te l l i t e images for the Al ice Spr ings , Aus t ra l i a , a rea .T h e results, s h o w n in t ab l e 4-II, i n c l u d e th e fo l low ing

obse rva t ions .1. M a n y more faul ts were interpre ted f rom S190B

pho tographs t han f rom a ny o the r t ype o f image .2. W h e n fa u l t s shorter t han 10 km are exc l uded

f rom com puta t ion , t he num ber o f f au l t s i n t e rp re t ed

T A B L E 4-11.—Comparison of the Num ber of Faults

Identified From Various Sourcesfor the

A rea of A lice Springs, A ustralia

(a) All sources

Source Nu mb er of faults identified

> 1 0 k m < 1 0 k m Total

M a p

L a n d s a t - 1

SI 90 A

S190B

264^

4x

7 2

3 9

2 64

71

65-i;:

1 4 , ;

(b) Comparison ofS190A and SWOB photographs

Source Num ber of faults in area New faults

Previously Detected N ot detected mterPreted

known

S I 0 A

S190B

63

6522

29

4 3

u ,

J O

1 1 4

(c) Comparison ofLandsat-1 and S190B photographs

Faults from

Landsat - 1

Faults detected

onS190B

Faults not

detected

onS190B

N ew faults

interpreted

onS190B

f rom each typ e of sate l l i te image is greater than thats h o w n on the geological map.

3 . A p p r o x i m a t e l y th e s a m e n u m b e r of k n o w n fau l ts

was de t ec t ed on S190A and S190B pho tographs . Manymore n ew fau l ts were in t e rp re t ed o n S190B than S190Aphotographs , p robab l y because th e h igh re so l u t ion o f

th e S190B cam era ma kes it easier to d i s c r i m i n a t e fau l tsf rom o the r l i near f ea tu re s . Approximate l y 50 p e r c e n t o f

th e fau l ts detected on S190B ph otogra ph s are shorter

t h a n 10 km.4. A l m o s t 7 0 p e r c e n t of the faul ts de tected by

an a lys i s o f L andsa t -1 image ry we re a l so i n t e rp re t ed o n

S190B p h o t o g r a p h s . H o w e v e r , th e t o t a l n u m b e r o f

faul ts de tec ted on S190B pho tograph s i s tw ice t ha tdetected o n L a n d s a t i m a g e r y .

Merif ie ld an d L a m a r (ref. 4-12)conduc ted ex t ens ivef ie ld studies in an effort to de termine the or igin of thel inear s they m app ed f rom S ky l ab pho tog raphs o fsou the rn Cal i fo rn i a . A l though u nab l e to assign a cause

to a l l l i near s , t hey d id corre late many l inears wi thfau l ts , fo l i a t i on , an d close ly spaced f rac tur e se ts. Fa ul tswere i nd i ca t ed by top ograp h i c scarps; o f f set d ra inage o rr i dges ; l i near va l l eys and mounta in f ron t s ; con t ras t i ngtone, co l o r , and t ex tu re ; and vege t a t i ona l d i f f e rencescaused b y ground wate r b l ockage .

Structural and Tectonic Synthesis1

Resul ts o f pho togeo l og i c ana l ys i s have shown tha t

S kylab p h o t o g r a p h s a re val uab l e fo r p r e p a r a t i o n o f

regional s t ruc tu ra l maps . From such maps , geo log is t s

can se lect areas for de tai led ground studies, leading todef in it ion of targets fo r fu r the r exp l o ra t ion of p o t e n t i a l

m i n e r a l resources or suspected geological hazards.New maps based on E R E P d a t a of areas that have

been studied previously can lead to re in t e rp re t a t i ons ofth e geology and new hypo these s of reg iona l s t ruc tu re .D u r i n g a s t ruc tu ra l ana l ys i s of the A n a d a r k o B a s i n

(Ok l ahoma-Texas) , Co l l i ns et al . (ref. 4-13) found asu bs tan t ia l cor re spondence be tween l i neament s in-

t e rp re t ed f rom the pho tographs and fau l t s i nd i ca t ed byseismic data. This corresponden ce suggests a greater

SO

Structure refers to i nd i v i d ua l features su ch as folds, faul ts , orjo i n t swa rm s . Tec to n i cs refers to the origin of large-scale s t r uc t u r a lp a t t e rns o f s u b c o n t in en ta l s i ze — t h e a r r a n g e m e n t of m o u n t a i n belts,basins, and fau l t sy s t em s .




a m oun t o f no r m a l faul t ing on the nor the rn s ide of thebas in than h as been recognized. Th e l ineaments andfaul ts could ha ve a s soc ia ted s t ruc tura l c losures , wh ich

m i gh t c on t a i n hy d r oc a r b on a c c um ul a t ions . F u r t he r e x -p l o ra t ion to te s t t he hyp oth es i s appea rs to be war ranted .

W h e t h e r or not a pa r t i c u l a r f r ac tu r e originated by

t ens ion or by shea r i s much deba ted . De te rminingw h i c h mo del is app l icab le to the rocks in an area is ani m p o r t a n t s te p t owa r d de t e r m i n i ng th e o r i e n t a t i on o f

th e stresses t ha t were respons ib le for the deformat ionof the rocks . M c M u r t r y and P etersen (ref . 4-14) statedt ha t l i ne a m e n t s , f racture t races , and j o in t s mapped onS kylab p h o t o g r a p h s are coinc ident in direct ion in ana rea of the A l l egheny P la teau . They po s tu l a te tha t ther e l a t i onsh ip is more cons i s t en t wi th a t ens iona l than a

shear model of or ig in .

The E R E P pho t og r a phs p r ov i de d s y nop t i c v i e ws o fmap ped l ineamen ts ( com plex , long , rec t i l inea r f rac turezones) . Geologis ts bel ieve these s t ructures are i m por -

t an t to unders tanding the g loba l t ec tonic sys tems , buttheir natur e and origin are not yet wel l es tabl ished. Leeet al . ( ref . 4-2) noted that l ineaments cu t across you ngs t ruc tu ra l t rends in the Colorado Front Range . The

origins of these l ineaments are not k n o w n , but theyprobab l y resu l t f rom recur ren t mov emen t a long o ldfracture systems.

In areas wh ere l inea rs and l ineam ents can be show nby f ie ld studies to be faul ts , the k ind and am ou nt of dis -p l a c e m e n t a l ong the m m a y still be a matter of conjec-ture. W hen cons ide r ing severa l t ec tonic hypotheses , i tis necessary to de t e r m i ne not only th e sense of displace-m e n t ( ho r i zon t a l o r ver t i ca l movement ) bu t also th e

length. Direct evidence of the sense of hor i zonta l d i s -p l acement a long faul t s could seldom be ob ta ined f romSkylab photographs . In the Peninsula r Ranges , south-wes te rn C a l i forn ia , M er i f i e ld and Lamar (ref . 4-12)used S k y l a b pho t og r a phs and Landsat images to dis-cover four faul ts in the basement rocks and to deter-mine from fieldwork the direct ion of displacement (f ig.4-6). They noted a regiona l a l inemen t of features poss i-b l y r e v e a l i n g u n r e c o g n i z e d s e g m e n t s o f t h e S a nAnd reas Fau l t sys tem southeast of the Salton S ea alongwhich p redom inant r ight -hor i zonta l s l ip i s kno wn to oc -cur.

Abde l -Gawad and Tubbes ing ( re f . 4 -15 ) ana lyzed

Landsat imagery and S kylab photog raphs for a l a rgearea of the Southwes te rn Uni ted S ta tes and nor t h -wes te rn M ex ico ( f ig . 4 -7). L inea rs in te rpre ted as faul t swere used to develop a tectonic m odel rela t ing major

faul t zones to f r a gm e n t a t i on a nd ro ta t ion of cru s ta l

blocks . The m ode l supp or t s the in te rp re ta t ion tha t theTexas shea r zone is one of three elements in a broadzone of deformation 2000 km long and 250 km widet ha t t r e nds no r t hwe s t from t he Gul f of Mex ico to the

Transverse R anges in Californ ia . The zone i s pos tu l a ted

to have a left- lateral offset of 500 km. The invest igatorssuggest that th e M oj a ve block and the S ie r ra b lock m ayhave ro ta ted 25° coun te rc lockw ise and the C oloradoPla teau , 15° c lockwise .

L ineaments have been ex tended specu la t ive ly bysome a utho rs for cons ide rab le d i s tances b eyond the i rk now n l i m i t s . H op p i n et al . (ref . 4-4) used E R E P p h o t o-graphs to tes t some of these p redic t ions . No evidence ofan ex tens ion of the N y e - B o w l e r l i n e a m e n t east of itspre sen t l y m a p p e d l i m i t in the P r y o r M oun t a i n s c ou l dbe f ound on an S190B color scene of the nor t he r nBighorn Mo unta ins in W yom ing. O ther l ineame nts inthis region a lso app ear to be l imited in length. Ex ten d-

in g l ineaments to great distances on the basis of analys isof space photographs m a y b e u n w a r r a n t e d .

The nature of geologic s t ructures is a key to under-s tanding th e location and types of past movements t h a tare now inac t ive . There are , however, geologic s t ruc-tures ac t ive ly forming tha t are evidence of crus ta lmovement . (See th e subsection on ea r thquake haza rds . )Surface di sp lacement not re l a ted to know n fau l ts can beinferred f rom the d i s t r ibu t ion and occ ur rence ofyo u th f u l l andform s . In U tah , Jensen and Lay lander(ref. 4-16) noted that recent a l luvia l fans cover old LakeBonnevi l l e t e rraces and a re in te rp re ted a s indica t ive ofrecent regional up l i f t of the W asa tch Range . Such infor -

mat ion may l ead to a be t t e r unders tanding of Ea r thdy na m i c s .

Photo l inea r maps of southwes te rn Gua temala andCh iapas docum ent the s t ruc tura l com plex i ty of thej unc t i on of the Cocos, Amer icas , and Car ibbean p l a tesand show th e s t ruc tura l re l a t ionships to volcanicregions. Stoiber and Rose (ref . 4-7) found that th epho t o l i ne a r pa t t e r n s w i t h i n th e Cent ra l Amer icanvolcanic cha in suppor t t he i r s egmented model of theBen io f f zone by s howi ng a concent ra t ion of t ransverse,

north eas t - t ren ding l inears in the predicted locat ions .Tectonic synthes is , one of the final goals of s truc-

t u ra l ana lys i s , begins w i th mapping on the bes t Skylab

pho t og r a phs f o l l owe d by field check ing , de ta i l ed map-p ing of key areas, in te rpre ta t ion , and ver i f ica t ion of hy-potheses. Th e resul t in g regional geological ma ps are ex-cel lent for such a synthes is .

G E O L O G Y AND H Y D R O L O G Y 137



F I G U R E 4-6.—S190B color - inf rared photograph o f the Peninsular Ranges in southwestern Cal ifo rnia, showing the major faul ts and l inears(SL3-87-111).

1 3 8 S K Y L A B E R E P I N V E ST IG A TI O N S S U M M A R Y



A Town

---- Dra inage

Known fau l t

-- - Fa u l t or linear in fer red

from E R E P pho tog raphs

s f e ^ j f o £ . * m

115 114

Long i tude, d e g W

F I G U R E 4-7 .—M a p of the Southwestern Uni ted States a n d n o r t hwes t e rn M exi co sho wi n g k n o wn fa u l ts a nd l ineaments . T he l ineaments were

interpreted from Skylab photography and are possibly fault zones.




Rock Types

A major e f for t in r e m o t e sensing has been directed

t owa r d th e ident if icat ion and discriminat ion of rocksand minera l s . Di sc r imina t ion is the separat ion of onerock type from another; ident if icat ion is the class if ica-

t ion of a spec i f i c rock or minera l according to uniquep h y s i c a l propert ies . The resul ts of this effort show tha tde ta i l ed informat ion i s needed for the d i s c r imina t ionand ident i f i ca t ion of rock types . Mos t a t t empts at rockdi sc r imina t ion a re made for reg iona l mapping invento-ries, whereas most minera l ident i f i ca t ion i s made forexplora t ion for a s ingle type of mater ia l .

A s described by M orrison et a l . ( ref . 4-9) in the GreatPlains States, by Morr i son 2 in Ar izo na , and by Lee e t a l .( ref . 4-2) in Colorado, most regional mapping is con-duc ted a t t he S ta te government l eve l or by pr iva te ex -p lora t ion com panies . The d i s t r ibut ion of a l l sur facemate r i a l s in the a rea i s examined . Spec ia li zed rock- type

or sur face - type maps are prepared for specif ic purposes ,such as select ing sites sui table for locat ing p u bl ic

ut i l i t ies , provid ing cons t ruc t ion ma te r i a l s , o r rout ingn ew h i g h w a y s .

The wor k of Jensen and Laylander (ref . 4-16) andBechtold et a l . ( ref . 4-17) i l lus tra tes the efforts of pri -va te interests in loca t ing deposits of minera l s tha t m ayhave potent i a l va lue . Us ing the i r approach , an in -vestigator searches fo r areas where geological events

al tered th e compos i t ion or s t r uc t u r e of the rock in sucha way that i t serves as a host rock for the ore min erals orhy d r oc a r b ons . W he n an area of potent i a l in te res t hasbeen located, intens ive geophysical and field surveys

are in i t i a t ed to provide more de ta i l ed informat ion onw h i c h to base deve lopment p l ans .Sky l ab inves t igators used t he cha rac te r i s t i cs of

sunl ight reflected from surface materia ls as a means ofid en t i f y in g a nd m a p p i ng roc k a nd m i ne r a l ty pe s . This

process has been used fo r m a n y y e a rs in field ident i f i ca -t ion and a i rc ra f t reconna i s sance to de te rmine the co lor ,b r ightnes s , t ex ture , and geographica l pos i t ion of themate r i a l . A pre l im ina ry iden t i f i ca t ion can be m adefrom t h i s informat ion by an exper ienced geologi s t .H owe ve r , m a ny more f ield and l abora tory tests are re-quired to make a posi t ive ident if icat ion after an area ofspecific interes t has been defined.

R. B. Morr ison, "A pp l i ca t i o n of Skylab E R E P P ho t o g ra phs toStudy of the M o d e r n Epi s ode of Accelerated Erosion in SouthernA ri z o n a , " unp ub l i s h e d F i na l R epor t , NASA-USGS A g r e e m e n tT-4113-B, 1975.

The d i s c r imina t ion fac tors examined by mos t Skylab

inves t igators were those of vis ible color and brightness .Color and brightness of the remote ly sensed sur facewere compared with the characteristics of a k n o w ns tanda rd . Iden t i f ica t ion w as then m a de on the basis ofth e degree o f s imi l a r i ty be tween th e tes t materia l and

the s tandard. The work of Lambert e t a l . ( ref . 4-6) inAust ra l i a and the examina t ion of Nevada sur facemateria ls by Quade et a l . ( ref . 4-1) exemplify this tech-n ique . Color photographs f rom the S190A and S190B

camera sys tems w ere comp ared w i th aircraf t colorpho tograph s and w i th f i e ld pho tographs and sam ples ofma te r i a l s. A l though pr im ary co lor compar i sons wereposs ible , a tmospheric dispers ion of l ight and laboratoryprocess ing of the pho t og r a phs m od i f i e d th e Skylab

pho tograph color , co lor ba l ance , and br ightnes s to suchan ex tent tha t the pho tograp hs could not be used a s ac -c u r a t e i n d i c a t o r s o f t he s a m p l e d g r o u n d c o l o r .L abora to ry mod i f ica t ion of the Skylab photog raph col -

ors w as mad e to matc h th e colors vis ible in fie ld ex-a m i n a t i o n . I t was found tha t , wh en one spec i f ic s amplea rea w as co lor -correc ted to ma tch the ground sam ple ,other sam ple areas m igh t be degraded in color represen-t a t ion . High-qua l i ty photographic proces s ing was con-s idered to be essent ia l to the inte rp reta t io n. Quad e et a l .( ref . 4-1) stressed t ha t d i f fe rences in pho t og r a ph c o l o rsenhance an in te rpre te r ' s abi l i ty to separate one surfaceun i t from another , even though the co lors may not ex -ac t ly ma tch ground color (figs. 4-2 and 4-8).

To emph as ize specific types of rocks and to enh ancethe contras t between d i f fe ren t mater ia l s , a va r i e ty ofc o l o r c o m b i n a t i o n s a n d s i n g l e - b a n d w i d t h s p e c t r a l

regions was used . Mu l t iban d pho tograph s in the vis ibleand nea r - inf ra red spec t ra l reg ions were used in com-b ina t ion and separately by L ee et a l. ( ref. 4-2) , Housto net al . (ref. 4-5), Bechtold et al . (ref. 4-17), Goetz et al.(ref. 4-18), Lee and Raines (ref . 4-19) , and others top r oduc e pho t og r a phs t ha t enha nc e d th e di f fe rences b e -tween ad j acent sur faces fo r visua l in te rpre ta t ion . A s a n

e x a m p l e , a n i m p r o v e m e n t i n d i s c r i m i n a t i o n o fa l l uv ium-cove red and h yd roth e rm a l ly a l te red a reas wasevident in some fa l se -color -compos i t e photographsformed from th e b l a c k - a n d -w h i t e S 190A p ho t og r a p hs .This t echnique enab led th e in te rpre te r to va r y th eemphas i s w i t h i n th e four spectra l regions to accentuatethe des ired color balance. Pa rt icu lar value was noted forth e S190A photograph s in the 0.6- to 0.7-fj.m b a n d w i d t h .

Disc r imina t ion of red beds was imp rov ed us ing the in -frared spectra l regions because of the d is t inc t ive reflec-t ance of these rocks .

1 40 S K Y L A B E R E P IN V E S T I G A T I O N S S U M M A R Y



F I G U R E 4-8.—S190B color photograp h of the Prescot t , Arizona, area, taken at 16:53 GMT on Dec ember 4, 1974 (SL4-90-306). Differences intone an d t ex tu r e can be used to discr iminate between surface mater ials . Sites A and B are sedimentary rocks , s i te C is mostly basalt, an d site Dis an area of gran i t e . Th e approx imate area s hown in figure 4-10 is outl ined.






minerals . A very smal l percentage of i ron may domi-n a t e th e r e f l e c t a nc e r e s pons e m e a s u r e d a t t hespacecraft , as exemplif ied by f igure 4-9.

Th e EREP inves t iga t ions of atmospheric effects byThomson (ref . 4-20), C han g and Isaacs (ref. 4-21), andothers i l lus tra te th e inf luence of a tmospher i c absorp-tion

andscat tering

onspectral reflectance data (fig.

4-10) . Many major a tmospheric effects coincide withthe spectra l bands required for accurate iden t if icat ion ofrocks , which suggests that future progress in rock- typeclass if ication from orbi ta l a l t i tudes should b e l inkedclosely to atmospheric-correct ion models based on sur-face al t i tude and aerosol absorpt ion.

E X P L O R A TI O N FO R M I N E R A L A N D E N E R G YRESOURCES

E x p l o r a t i o n f o r e c o n o m i c a l l y u s e f u l m i n e r a l

resources involves surveys or reconna issance s tudies oflarge regions to locate th e much smal ler areas t ha t m aybe worth th e expense of detailed study. Geologistsrout ine ly use surface t raverses , geophysical surveys ,and interpreta t ion of aeria l photographs fo r reconnais-sance. P h o t o g r a p h s of the E a r t h ob t a i ne d f r omspacecraft are useful because they can provide v iews oflarge areas under uniform l ight ing condi t ions withspat ial resolut ion adequate fo r photoin te rpre ta t ion . TheEREP inves t igators s tudied different types of data todetermine th e mos t useful spa tial resolution, spectralresolut ion, scale, and forma t fo r resource explora t ion .Their results indicate that color or color-infrared, syn-opt ic , stereoscopic photographs w i th approx ima te ly 10-m ground resolut ion are the best tools fo r photoin-t e r p r e t a t i on . P os i t i ve t r a n s pa r e nc i e s a re bes t forlaboratory s tudy, 23- by 23-cm posi t ive paper prints aremost useful for field checks , and larger paper prints arebest for compi l ing informat ion .

Mineral Explora t ion

Fracture sys tems (i.e., combinat ions of faul ts andj o in t s ) provide pa thways fo r ore-bearing f luids and tendto localize deposition of ore minerals . Fractures may beexpressed at the Earth ' s surface as s tra ight val leys if the

materia l a long th e f rac ture is crushed or altered, or asstraight ridges if the f rac ture is filled with resistant veindeposits . Straight topograph ic features such as these are

vis ible on EREP photographs a s l inea rs tha t can bemapped, and the i r s igni f i cance can be de te rmined byfield check . Fo r example, S toiber and Rose (ref. 4-7)found that t rends of l inear features mapped on S190Aand S190B ph otograp hs agreed w i t h previous ly mappedt rends of l ead-z inc , go l d -s i l ve r -mercury - t i n , and copperveins in Centra l America . Pros t ( in ref . 4-2) found agenera l cor respondence be twee n d ens i ty of l inears andlocat ion of mineral dis t r icts in Colorado. He and otherinvest igators emphasize the necess i ty of careful fieldcheck ing to e l imina te l inea r fea tures tha t do not repre-sent the su rface express ion of geological fracture s orrock-body contacts .

Bechtold et al . (ref. 4-17) studied S190A and S190Bphotographs and S192 imagery of Ca l i forn ia , Nevada ,and Ar izona to def ine combina t ions of l inea r and cur -v i l in ea r features that might be correla ted w i t h m i ne r a ldeposi ts . As an example, they described a nearly circu-lar topographic feature near Hunter Mountain (f ig.4-11) in the Pan am int R ange, Cal ifornia . S imilar ci rcu-la r features ma rk the loc at ion of bodies of intru s ive ig-neous rocks in the Southwestern United States ; many ofthese rock bodies are permea ted w i t h low-grad e (0.5 to3.0 perce nt) cop per su lf ide and/or molybdenum sul f ide .Th e c i rcu la r topographic features are caused by eros ion

of f rac tured rock . Some fractures are l ined by soft ,a l tered ma teria l ; others are f i l led w ith resis tance qua rtz.The net resul t is a dense n e t w o r k of short , s t ra ight , andcurv i l i near va l l eys and r idges th a t out l ine the potent i a lore body . The Hun te r M oun ta in fea ture i s not d i f fe ren-t ia ted from other g rani t ic bodies in the area (f ig.4-1 l (d )) , a l though i t is eas i ly dis t inguished o n theS kylab photographs . F ie ld checks showed tha t copper

and i ron sulf ides and their a l tera t ion products occurm o s t of the way a round th e pe r i phe r y of the c i rcu la rbody. Features such as these are targets fo r m o r edetai led invest igat ion because they m ay represent large,h i dde n ore bodies.

Another useful indicat ion of poss ible large, low-grade ore deposi ts is an area of al tered materia l at thesurface (ref. 4-22). The al tera t ion is caused by c he m i c a lso lu t ions in heated water that spread from th e source ofmine ra l i za t ion into surrounding rocks . Surface indica-t ions of a l tera t ion zones range from br ig h t ly colored inshades of red and ye l low due to ox ida t ion of i ron

minerals , to white resul t ing f rom bleaching of the rocks

and deposi t ion of clay minerals . In reference 4-23, Le-vandowski and Borger repor t t ha t compute r -a idedan a lys i s of S192 data from the San Juan M oun tains ,

GEOLOGYAND HYDROLOGY 143



•x

0 15 \Approximate scale, km

FIGURE 4-10.—Imagery of the Prescott, Arizona , area, (a ) S192 image taken at the t ime of the photograph in figure 4-8 and presented in a con-ical fo rma t of ba nd 11 (1.55 to 1.75 ^ m i. Thi s band has been sugges ted as having excel lent potent ial for rock- and mineral - type discr iminat ion,(b ) False-color image of the da ta s hown in f igure 4- 1 i l i a > . This type of e n h a n c e m e n t can be used to i m p r o v e th e i n t e rpr e t ab i l i t y over an e x t e n -sive

scene,(c) Color composite of S192 data of the ou tline d area in figure 4-8, p resented in a conic al form at of visib le-wavelength ban d 6 (0.68 to

0.76 M m ) , band 3 (0.52 to 0.56 / u r n ) , and band 1 (0 .41 to 0 .46 ^m ) . The subdu ed scene co ntras t , pa r t ial ly caused by the inf luence of atmo sphe r icscat ter ing, is note wo rthy , (d) Color composi te of the area show n in f igure 4-10(c), using band 12 (2.10 to 2.35 ^m) and band 8 (0.98 to l . O S ^ m ) .

The s ignif icant increase of contrast f rom figure 4-10(c) is ev ide nt.




A p p r o x i m a t e s c a l e , km

FIGURE 4-10.—Concluded.




i s s i . - ? /.j&ffi&fjti. ,' H.

F IGUR E 4 -11 .—Anomalous c i r c u l a r f ea tu r e near Hunter Mounta in in the Dea th V a l l e y area of C a l i f o rn ia , (a ) S190B color photograph(SL4-94-013). The area shown in f igure 4-ll(b) is out l in ed. 0) ) Enlargemen t of c ircu lar featu re, (c ) View looking westward across t he c i r c u l a rfea t u re from a mineral prospect ing pi t on the r im of the feature (NASA S-75-31982). (d) Geological map of the area in which the c ircularfeature is loc a ted , c ompi l ed f rom prev ious ly pub l i s hed sources ( r e f . 4-17).




. • • •

F I G U R E 4-11.—Continued.

Colorado , a l lowed the de l inea t ion o f a l t e ra t ion zones as-sociated w ith ve in m inera l i za t ion , provided ad equa tefield s tudies and grou nd - t ra in in g samples were ava i l -able . Inves t iga tors w h o s tudied Sky lab image ry fo r colorclues to poss ible mineral deposi ts include Quade et a l .(Nevada; ref . 4-1) , Lee et a l . (Colorado; ref . 4-2) ,Hous ton et al. (W yom ing; re f . 4 -5 ), Lam ber t et al.(Aus t ra l i a ; ref. 4-6), Jensen a nd L a y l a nde r ( U t a h a nd

Nevada ; re f . 4 -16) , Bechto ld e t a l . (Ar izona , Nevada ,and Cal i f o rn ia ; ref . 4-17) , and Watson et al . ( N e va da ;

ref. 4-24). Figure 4-12 i l lus tra tes the a l tered zo ne associ-a ted wi th th e minera l i zed a rea in G o l d f i e ld , N e va d a , inc om pa r i s on w i t h p r e v i ous m a pp i ng . I t s hou l d b eemp has ized th a t co lor , a s do f rac ture pa t t e rns , form sonly one piece of evidence in a long cha in of logic t ha tmay l ead to the d i s covery of minera l depos i ts .




, * '• • " • • ' .

*<**: < IV

F I G U R E 4 -11 .—C ont inued .

Jensen and Laylander (ref . 4-16) repor ted that s tudyof S190A color photographs f rom th e Skylab 2 missionsuggested that por t ions of an area in the nor thern EganRange in N evada a re und er la in by l igh t- co lo red carbo -nate rocks rathe r than by dark-colored volcan ic rocks asprevious ly m a p p ed . This observation is s ignif icantbecause a large magnetic anomaly in the area coincidesa pp r ox i m a t e l y wi th the exten t of vo lcan ic rocks (ref .4-25). Jensen suggested that th e m a g n e t i c a n o m a l ymigh t be caused, in par t , by a body of igneous rock thatintrude d the carbonate rocks. I f so , min eral izat io ns imi l a r to tha t a t E ly , Nevada (25 km to the sou th ) ,m i g h t be present . Geologists f rom universi t ies , indus-

try , and governmenta l agenc ies p ro m pt ly inves t iga tedth e area. Fo r exam ple, Quade (ref . 4-1) enlarged th eS190A pho tographs to the scale of published maps (ref .4-26), compared them with aer ial photographs, and per -

formed a f ield check. He decided that the geology hadbeen ma ppe d correc t ly by Car lson and M abey (ref .4-25), t ha t th e magnet ic anomaly is c o i n c i d en t wi th out-crops of volcanic rocks, and that no min eral iz at ioncould be found in the ou tc rop p ing carbonate rocks . Ex-plora t ive w o r k is being con t inued in the area.

Pros t (i n ref. 4-2) investigated th e h y p o t h es i s t ha tanom alous redd ish or pinkish areas that are caused by aconcentrat ion of iron oxide and that occur in regionsmarked by dense f r ac tu re ne tworks m igh t be ind ica to r sof pote ntial ly econom ical ore minerals in central Col-orado. Anomalous reddish areas were observed onEREP co lo r pho tographs o f two tes t sites (C r i p p l e

Creek an d W eston Pass) . Field checks showed th at onesuch area was caused by iron oxide der ived f romwea ther ing of sulfide minera l s , one by iron oxide an dfeldspar , and two by f e ldspar a lone . Anomalous tan n ish

1 48 S K Y L A B E R E P I N V E S T I GA T I O N S S U M M A R Y



P a n a m i n t S p r i n g s

Q a l Al luv ium

P s P l i o - P l e i s to c e n e s e d i m e n t sP v P l i o - P l e i s to c e n e v o l c a n i c s

g r M e s o z o i c g r a n i t i c s

I~ P P a l e o z o i c rocks— M a p p e d f a u l t s

I m a g e r y a n o m a l y





FIG U RE 4-12 .—G o l df i e l d , N ev a da , a r e a , (a ) S190A color photograph (SL3-28-057). ( b ) Map sho wi n g areas of hy dro t he rm a l a l t e ra t i o n an d

location of ore deposits.




1 1 7 1 5 ' W 11 7 1 0 ' W

37r 45' N -

(b )

Surface projections

of ore -bear ing areas

F IGUR E 4-12 .—C o nc luded .

areas in th i s reg ion were a t t r ibuted to quar tz - r i ch peg-mat i t e s and l ight-co lored sedimenta ry rocks and altered

in t rus ives .No minera l f inds based on the s tudy of EREP da ta

have been repor ted . T h e t h ree exam ples j us t descr ibedi l lu s t r a te the use of space data in developing testable h y-potheses of po tent i a l mine ra l occurrences . Exp lora t ionp r og r a m s ar e usual ly of 5 to 10 y e a r s du r a t i on , and it isant i c ipa ted t ha t u s e o f the E R E P da t a wil l lead to somes ignif icant discoveries over the next decade.

Pet ro leum Explora t ion

A l t hough hy d r oc a r b on a c c um ul a t i ons c a nno t b edirect ly detected, t h e i n t e r p r e t a t i on o f E R E P da t a c an

p r ov i de i n f o r m a t i on on regiona l l i t ho logic and s t r uc -tu ra l re l a t ionships and quick ly draw attention toanomalous features and areas that are of the greates t in-t e res t in pe t ro l eum exp lora t ion . To be usefu l , ER EP in-f o rmat io n m u s t be integrated effectively w i t h a w i d evariety of other types of data (geophysical , subsurfacegeology, and p r oduc t i on h i s t o r y ) a n d i n c l ude d w i t h i n

t he s t ruc ture of a ra t iona l explora t ion s t ra tegy . The ad-vantages of Sky la b da ta can be obta ined with l i t t le addi -

t ional cost to a conve nt iona l explorat ion program ( re f .4-13) . Cost -saving benefi ts accrue f rom decreases inreconna i s sance t ime , in s e ismic ex plora t io n , and inlease-acquis i t ion expenses . Th e cost savings have beenest imated to be as great as 40 percent in an explorat ion

program ( t ab le 4 - I I I ) .

GEOLOGY ANDH Y D R O L O G Y 151



FIGU RE 4-13.— Anad arko B as in of wes tern O klah om a, (a) S190B color photograp h (SL4-90-144) . (b) Map s h ow i ng l inear fea tures and c ircularanomal i es in t e rpr e ted from Sky lab pho tography . The l inear features m ay represent fault zones, and the circular anomalies ar e st ructures possi-bl y containing oi l or gas .








TABLE 4-III.—Comparison ofEstimated Costs of

Petroleum Exploration Using Skylab and

Con ventional Exploration Techniques

Exploration m ethod Estim ated cost

Co n v en t i o n a l

Airc raf t p h o t o i n t e rp re t a t i on of 80 000 km 2 $ 64000

Reco n n a i s sa n ce surface geology of 80 000 km 2 200 000

Reco n n a i s sa n ce s e i smic s u rve y of 4600 km 2 420 000to locate a n o m a l i e s

Detailed seismic survey of 600 km 2 720 000

Total $1404000

Skylab

In t e rp re t a t i on of data i n c lu d in g c o m p a r i s o n $ 24000

wi th a i rcra f t p h o t o g r a p h sAirc raf t photointerpreta t ion of 6000 km

215 000

Reconnaissance surface geology of 6000 km2

21 000

Detai led seismic s urve y of 600 km2

720000

Total $780 000

In t he s t u d y of the A n a d a r k o B a s i n in O k l a h o m a ,

Co l l in s et al. (ref. 4-13) found the S190A and S190B

p h o t o g r a p h s to be exceed in g ly v a lu ab le fo r o b t a i n i n g a

rapid geological assessment o f large areas and for con-

d u c t i n g a re la t iv e ly d e ta i led s tu d y o f specif ic areas of in-

te r est . L in ea r s in te rp r e te d f ro m S ky lab d a ta a n d L a n d -

sat imagery relate wel l to joints and subsurface faults.

Some kn o wn su r f ace f au l t s were map p ed and several

u n k n o w n f au l t s were in f e r r ed f ro m S ky lab d a ta b y Co l -

l in s et a l . (f ig . 4-13). Field s tudie s show tha t many longl in ea r s co in c id e wi th d i s tu rbed zones in su r face ro ck ex -

posures; these may represent majo r f au l t s at d e p t h .

To n a l and d ra in ag e an o mal ies were detected in m a n y

p h o to g rap h s . C i r cu la r d r a in ag e p a t te rn s a n d to n a l

an o mal ies sh o w th e h ig h es t co r r e la t io n w i t h k n o w n h y -

drocarbon occu rrences . C oll ins et a l . (ref . 4-13) s ta ted

t h a t l i t h o l o g ic i n t e r p r e t a t i o n s fr o m t h e E R E P d a t a a r egene ra l ly a c c u r a t e b u t d o n o t a l w a y s m a t c h p u b l i s h e d

i n t e r p r e t a t i o n s . These in te rp r e ta t io n s in d ica te a r eas

w h e r e r e m a p p i n g is d es i r ab le to ver i fy new ideas

d er iv ed f ro m th e r eev a lu a t io n o f su p p o sed ly wel l -kn o wn p e t ro leu m p ro v in ces ( r e f . 4 -27 ) .

Us in g S1 9 0A p h o to g rap h s , Riv ereau , o f th e In s t i tu te

Fran ca is d u Petro le ( in ref . 4-28), rein terpreted th e

geology o f a Permian bas in o n th e so u th wes te rn bo rd er

o f th e F ren ch cen t r a l mass i f . I n th e cen t r a l so u th ern

p a r t of the basin, a rela t ively th in ly bedded u n i t (u n i t A,

fig. 4-14) composed of f ine sedim ents (s i l ts tone and

c l ayey sandstone) is s u r r o u n d e d b y t h i c k l y bedded

san d s to n e to th e wes t an d n o r th (u n i t B) an d co n -

g lo mera tes to th e so u th (u n i t C) . U n i t A was co n s id er edby field geologists to represent l a te r a l l i th o lo g ica l

ch an g es wi th o n ly th e wes te rn bo u n d ary be in g s t ru c -

t u r a l l y c o n t r o l l e d b y a n o r t h w e s t - t r e n d i n g f a u l t (F l ) . Aco n v en t io n a l p h o to g eo lo g ica l map of t he area showedt h a t u n i t A was v ery h o mo g en eo u s an d th a t i t was

crossed by n u mero u s f au l t s h av in g a n o r th w es t t r en d ,

t h e r e b y c a u s i n g s m a l l d i s p l a c e m e n t s o f b e d d i n g .

H o wev er , becau se of the s t r ike of bed d in g in u n i t s Aan d B an d th e same d is lo ca t io n o f bed d in g cau sed b y

t h e n o r t h w e s t e r l y t r e n d i n g f a u l t s , n o t h i n g else w as

su sp ec ted abo u t th e r e la t io n sh ip be tween u n i t s A an d B.

Th e syn o p t ic v iew of the S kylab p h o to g rap h s (an d , to alesser degree, of the L a n d s a t i m a g e r y ) sh o w e d the dis-t inc t r eg u la r p a t te rn o f u n i t A , wh ich i s bo u n d ed o n a l l

sides b y stra ight l ines . From these p h o t o g r a p h s , i t was

obvious to th e in v es t ig a to r th a t th e d is t r ibu t io n o f u n i tA is s t r u c t u r a l l y c o n t r o l l e d by faul t ing. It is c u r r e n t l ybel ieved that unit A occupies a co l lapsed par t of the

basin in w h i c h the top sediments of the trough have

been p r ese rv ed f ro m ero s io n . Th eref o re , u n i t A sh o u ld

n o lo n g er be ch ro n o lo g ica l ly co r r e la ted w i th u n i t B ; th a t

is , un it A no longer ap pea rs as a local l i tho logica l var ia-

t io n o f u n i t B . I t i s p ro bab le th a t u n i t A i s yo u n g er than

u n i t B an d h as been r emo v ed f ro m th e to p o f u n i t B ino th er p a r t s of the area a nd only preserved in the col-

l ap sed a rea . Riv ere au emp h as ized th a t , ev en th o u g h th e




r»

10

Scale, km

.-- Fau l t and l ineament^ L imi t ofTr iass ic F ormat ion

-*• ' L imi t of P e rm i a n trough v is ib le on Skylab imagery

&* • A rea o f unit A as discriminated fro m Skylab imagery

FIG U RE 4-14.—Portion of the Aqui ta ine Basin in southern France wi th an interpreta t ion of l i thologic contacts an d faul ts on an S190A photo-

grap h (SL3-34-321). Original scale, 1:320 000.




feature is v i s ib l e on Landsa t images , it is p r o m i n e n t inthe Sky lab ph otograp hs o nly because of the we l l -defined spectra l contras t in S190A color f i lm. The ap-pearance of the feature was enhanced by making fa lse-color compos i t es us ing va r ious combina t ions of theS 19 0A b l a c k - a n d - w h i t e p h o t o g r a p h s . D r i l l i n g a n d

geophys ica l surveys a re now underway in the a rea , andc o n f i r m a t i o n or nonc onf i r m a t i on o f t h is hy p o t he s i swil l be de te rmined f rom the resu l t s .

Ant i c l i na l fo lds of ten p rovide s t ruc tura l t raps for hy-

droca rbons . Numerous examples of fo lds mapped onS kylab photograph s can be found in E RE P repor ts ( e .g . ,refs. 4-4 and 4-5). Vargas (ref. 4-29) reports th e detec-t ion of l ineaments and dra inage anomal ies th a t may in -d ica te subsurface fau l ts and ant i c l ines in nor th -cent ra lBol ivia, an area undergoing act ive explorat ion for oi l

a n d gas. These inves t igators bel ieve that th e E R E Ppho t og r a phs wil l be of direct help in locat ing prospec-t ive s t ruc tures .

Explorat ion fo r Ge othe r m a l Energy

Th e ind i rec t m e thods u se d to search fo r m i ne r a l sand pe t ro l eum are also used to search fo r geotherma lenergy. In addi t ion , inves t iga tors are a t t e m p t i ng to useth e di rec t meth od of m a p p i n g h o t ground us ing the rma lscanners . A n e x a m p l e of i nd i r e c t m e t h o d s is p r ov i de dby Been told e t al . (ref. 4-17) for th e Coso Hot Springsarea in Ca l iforn ia (f ig. 4-15) . This is a we l l - k nown t he r -m al area that h as been s tudied thoroughly (refs . 4-30

and 4-31) . Evidence of recent volcani sm in the area in -

cludes lava f lows, vents, cones, h ot springs , and areas ofs teaming ground. F rac tur ing of the rocks is intense, andpatches of hydrotherma l ly a l t e red ma te r i a l occur . Th eCoso Hot Springs area is a potent ia l source of geother-mal power. S tudy of S190A and S190B photographs byBechto ld et al. ind ica ted tha t , 70 km south of Coso HotSprings , in the L a va M oun t a i n s , t here is a s imilar( though sma l l e r ) area of repeated volcani sm, in tensefractur ing, and hydrothe rma l ly a l t e red ma te r i a l ( f ig .4-15). A well dri l led in the 1920's revealed ho t rock andsteam at 120 m (ref. 4-32), but the resource w as nevercommerc ia l ly deve loped . S tudy of Skylab photographs ,

toge the r w i t h brief f ie ld check ing, suggests tha t an areaof a p p r o x i m a t e l y 15 km 2 may be p o ten t ia l ly explo i t ab lefo r geotherma l power .

M c M u r t r y and Petersen (ref. 4-14) analyzed S190Apho t og r a phs of the Susquehan na R iver bas in in Penn-sy l van ia to de t e r m i ne th e r e l a t i ons h i p of a wa r m s p r i ng ,

a large circular fea ture , and a ma jor l ineament ; and toes tabl ish the regional geologic s t ructure for use inde ta i led s tudies . Aer ia l t he rma l surveys and f ieldwork

a re c o n t i n u i n g to de te rmine the s i ze and s igni f i cance oft he t he r m a l feature.

D u r i n g t he Skylab mis s ions , p ar t icu la r ly S ky lab 4,some p r e da w n t he r m a l i m a ge r y w as obtained (f ig. 4-16)

that demonstra tes the suff iciency of the S I92 spat ia land the rma l reso lu t ions for d i s c r imina t ion of dif ferent

types of mater ia l on the Ear th ' s sur face . Dayt ime the r -

ma l im agery was ob ta ined over the Geysers geo therma l

powe r field in Cal i forn ia . Ana lys i s of t h i s imagery bySiegal et a l . ( ref . 4-33) demonstra ted that spots approx-

ima te ly 1 K w armer than the sur rou nding a reas can bedis t inguished (f ig. 4-17) . Co mp arison w ith S190Bphotographs , ae r i a l photographs , and previous f ieldm a p p i ng s howed t ha t m a ny of the w a r m spots coinc idew i t h s i tes of geothermal wel ls and s teaming ground.However , t hese known warm sites also are bare ofvege ta tion and , c o inc identa l ly , t end to occur on south-facing s lopes where solar heat ing is at a m a x i m u m .Ca lcula t ions indicate that solar heat ing can account forth e effects recorded by the S192 scanner. The resu l t s areencouraging because they suggest that s imilar , perhapsm o r e sens i t ive , predawn images might provide useful

clues to s ites for geotherm al e xp lora t ion . Such factors as

s lope direct ion (aspect) , s lope angle , previous weather( t empera ture h i s tory at the s i te , ra infal l ) , and vegeta-t ion will have to be cons ide red when us ing such the rm a limagery.

E N V I R O N M E N T A L G E O L O G Y

The use of E R E P da t a to identify and s tudy geologi-ca l hazards and the tes t ing of those data in engineering-and envi ronmenta l -geology appl i ca t ions a re descr ibedin this subsect ion. Geological hazards s tudied include

1 5 6 S K Y L A B E R E P I N V ES T IG A T IO N S S U M M A R Y



F IGUR E 4-15.—Coso Ho t Springs and the Lava Mountains , Cal ifornia, (a ) S190A photograph (SL4-76-078). (b ) Enla rgement of the Coso Ho t

Springs area.




FIG U RE 4-15 .—Co n c l u ded .

1 5 8 S K Y L A B E R E P I N V E S T IG A T IO N S S U M M A R Y





F IGUR E 4-17.—Geysers area in California, (a) S190B color photograph (SL4-92-335). (b) Portion outl ined in f igure 4-17(a).

(c ) SI92 image enha ncem ent of the Geysers area ( re f . 4-33) at app rox im atel y the same scale as f igure 4-17(b) .

F I G U R E 4 - 1 7 . — C o n t i n u e d .









f racture traces an d rela ted l ineaments cross ing th eC l a r k Hil l Reservoi r on the Savannah R iver , nor th ofA u g u s t a , Georgia . H e noted tha t ep icente rs o f some

e a r t hq ua k e s ( m a x i m um m a gn i t ude of 4 .5 on theR i c h t e r scale) that occurred in 1974 were plot ted in thesame a rea . The EREP da ta were be ing used to deve lop

field evidence for assess ing the causes of the earth-quakes .

Abdel -Gawad and Tubbesing (ref . 4-15) ident if iedsegments of faul ts in the western Mojave Desert adja-

cent to the San B e r na r d i no and San Gabr ie l Mounta insand the San Andreas Faul t zone . They produced mapsde l inea t ing specif ic areas of seismic risks based on

geomorphic evidence of recent faul t ing (vis ible breaksin th e surf ic ia l a l l uv i um an d surface rocks , s t ream

offsets, etc.). Mer i f ie ld and Lamar ( re f . 4 -12) mappedfau l ts in the Peninsula r Ranges of southwes te rnCal i f o rn ia and conduc ted ex tens ive f i e ld inves t iga t ionsto de te rmine the i r potent i a l fo r se i smic i ty . Us ing Skylab

pho t og r a phs , t he y f ound t wo p r e v i ous l y unm a ppe dfau l ts but de te rmined , through f i e ld s tudies tha trevealed no s igns of recent movement , that the faul tsposed l i t t le threa t for generat ing earthquak es . Quade e tal. (ref . 4-1) mapped l ineaments in the Mina region ofN e v a d a and then compared the map w i t h a p l o t o fe a r t h q u a k e epicenters for 1971-73. They found a corre-spondence be tween th e epicenter locat ions and the east-

nor theas t - t rending faul ts wes t an d southwes t of M i n a .

Lands lides.—Al though ER EP ph otographs genera l lylack the necessary spat ia l resolut io n and vert ica l exag-gerat ion (for s tereoviewing) required to s tudy smal llandsl ides , some posi t ive resul ts were reported. Large

landsl ides were recognized and mapped by Quade et a l .(ref. 4-1) , Hoppin et al . (ref. 4-4), Houston et al . (ref.4-5) , Lambert et al. (ref. 4-6), and Lee and Raines (ref .4-19) . M cM ur try and Petersen (ref . 4-14) noted a goodcorre lat ion be tween l ineaments observed on Skylabpho tograph s and Landsa t imagery and a zone of frac-

tured ma te r i a l t ha t w as col lect ing and c ha nne l i ngground wa te r . This zone appea red to be the cause oflandsl ides on slopes along a m a j o r h i ghwa y in Pennsy l -van ia . This exam ple aga in demons t ra tes th e usefulnessof id en t i f y in g l inear features in relation to specificgeological hazards .

Volcanoes.—Cassinis et al . (ref. 4-11) noted that anS190B color - inf ra red photog raph ( f ig . 4 -18) t aken overSicily s howe d an a nom a l ous l y lo w inf rared reflectance

in an area of Mount Etna tha t l a t e r e rupted . The in -ves t iga tors pos tu l a ted tha t th i s type o f a nom a l y m i gh tbe caused by stressed vegetat ion resul t ing from smal l

but con t inuou s amoun ts of vo lcanic gases f i l te r ingt h r ough th e soi l . They analyzed 1 7 anomal ies and f oundthat most were caused by d i f fe ren t vegetat ion assem-

blages ra ther than by stressed members of the s ametype. In an a t t e m p t to cor re l a te l inea t ions and e r up -t ions , t hey mapped and ana lyzed l inea t ions on thewes te rn f l ank of Mount E tna . I t was found tha t (1) themax imum dens i ty occur red in the e rupt ion zone , (2)the first effus ive ope n i ng of the Februa ry 1974 e rupt ionoccur red at the intersect ion of four l inears that were 0. 5

to 2.5 km in length, and (3) the vegetat ive anom al iescorrela ted well with the geomet ry of the l inea t ions .From these resul ts , th e inves t iga tors conc luded tha t

their hypothes is , which suggested volcanic gases couldstress vegetat ion and resul t in reflectance anomal ies ,m i gh t b e va l id , even tho ugh they were no t able to verify

it in this invest igat ion of Mount Etna. They did deter-

mine tha t th e rela t ionship between l ineat ions an d erup-tion features w as s ignif icant .

Stoiber and Rose (ref . 4-7) , us ing EREP photographsof the Gua temalan h ighland s , mapped c i rcu la r and a r-

cuate features that correla ted with dis t r ibut ions of earlyQua te rna ry and Tert iary volcanoes .

Engineering Geology

This discuss ion of engineering geology includes tun-nel-site s tudies and cons t ruc t ion ma te r i a l s inventory .

Tunnel-site studies.—Lambert et al. (ref. 4-6) usedS kylab photographs of the Snowy Mounta ins a rea ofAust ra l i a to prepa re s t ruc tura l maps for compar i sonw i t h de ta i l ed s t ruc tura l informat ion ob ta ined in the

construct ion of long tunnels . The tunnels , bui l t for i r -r igat ion and hydroe lec t r i c purposes , a re an average of24 7 m be low the sur face . The compar i son enab led the

invest igators to de te rmine d i rec t ly th e va lue of remotesensing in id en t i f y in g f rac tures of concern in tunnel -s i tes tudies . They concluded tha t "The com binat ion of three




factors: (1 ) m e a ns of measur ing and achieving accepta -b le s t a nda r ds of data qual i ty , (2) empi r i ca l ev idencetha t approx ima te ly 50 pe rcent of sur face fea tures wil l

be detected unde r g r ound , and (3) suff icien t resolut ion

to i dent i fy th e locat ion of these features indicates a po-tent ia l operat io nal role in 1:100 000 surv ey ma pp ing and

in engineer ing a nd mining inves t iga t ions . "Construction materia ls inventory.—Several investiga-

tors used S k y l a b pho t og r a ph s t o s t udy a nd m a p surf icia l

mater ia l s conta in ing sand and grave l , b ut very fe w usedth e pho t og r a phs specif ical ly to locate new sources ofthese deposi ts . Three inves t igators w ho spe n t con-s iderable t ime on this las t object ive reported worth-w h i l e resul ts . W o o d m a n (ref. 4-34) used th e photo-g r a phs of M a i n e to map mora ines and eskers, w h i c h areth e State's major sources of sand and gravel fo r roadconstruction. Cassinis et al . (ref. 4-11) used m ul t i -spectra l analys is of S190A photographs to i den t i fy andmap the loca t ions of anc ient r ive r channe l s in the Vene-

t ian Plain of I ta ly. As is the glacial mater ia l in Maine ,these old r ive rbeds are sources of sand and gravel fo rcons t ruc t ion and freshwater . Cass inis s ta ted that h ede te rmined for the f i rs t t ime th e regional extent o fthese resources . Furthermore, h e es t imated a cost sav-in g of 90 percent in locat ing the buried channels withSky l ab photograp hs a s compared to loca t ing them w i the lec tr i cal res i s tiv i ty surveys . W hi l e wor k ing in Puer toRico, Trumbull (ref. 4-35) was able to locate coral reefs,offshore sand and gravel deposi ts (poten t i a l ly a va lua -b le resource ) , and areas of coastal erosion, and to iden-tify pa t t e rns of se d im e n t t ranspor t .

Ge oe nv i r onm e n ta l M a pp i ng

T h e ER EP photographs were used wi th va ry ingdegrees of success in several geology studies in wh i c hsurface geological features of environmental interes twere examined . Among th e m o s t s ignificant resul ts arethose repor ted by Morrison (ref. 4-9). H e us e d E R E Pp h o t o g r a p h s in c o n s t r u c t i n g e r o s i o n - s u s c e p t i b i l i t ym a p s of areas of southeas te rn Arizona

2and, in conjunc-

tion w i t h associates from si x Great Pla ins and M i d -western States , in pre par ing analyt ic al -geo mo rph ologymaps of areas within the six States (ref. 4-9).

The m a ps of Arizona combine informat ion on soiltypes , surficial deposi ts ( inc lud ing part icle s ize andcharacter of the deposi ts for several meters below the

soil prof i l e ) , and occurrences of exposed bedrock. Them a p s a lso provide back ground da ta on the suscept ib i l i tyof various types of surface materia ls to erosion andhence , on the potent i a l magni tude of the m ode r n ac -celerated-eros ion problem in southeas te rn Ar izona . A d -

d i t io n a l ly , the maps indicate the ease of excava t ingnear-surface materia ls for construct ion. The maps wereprepa red by di rec t photo in te rpre ta t ion of 1:250 000-scale Skylab pho t og r a phs u s i ng a s tereoplot ter and w i t h -out su pple men ta l ground cont ro l . Publ i shed geologic re -ports and maps were then used for construct ing deta i leddescr ip t ions of the m a ppe d un i t s . These m a ps offer th eland use planner or manager a low-cost tool because

they can be prepa red in a por t ion of the t ime requi redby s tanda rd f i e ld s tudies and map-prepa ra t ion pro-cedures . An example of one of these map s is show n infigure 4-19; th e e x p l a na t i on of the map uni t s is con-ta ined in table 4-IV.

Th e maps prepa red fo r areas of the Great Pla ins andMidwestern States (e.g., fig. 4-20) show surficialfeatures and contain r a t in g sys tems (table 4-V) for eachm ap u n i t in terms of l imita t ions or advantages oft o p o g r a p h y , a v a i l a b i l i t y o f s h a l l o w g r o u n d w a t e r ,avai labi l i ty and qu a l i ty of gravel and rock, s lopes tabil i ty , founda t ion condi t ions , ease of excava t ion ,road construct ion, surface drainage, and soi l ( internal

dra inage , erod ibi l i ty of soils , and sites for sani tary land-fills, sewage lagoons, and sept ic tanks) . Th e maps werep r e pa r e d w i t hou t field s tudies b y us ing ancil lary infor -mation such as topographic maps , geological and soi lmaps , reports , and h ig h -a l t i tu d e aeria l photographs incon junc t ion w i t h t h e E R E P p ho t og ra phs . They conta ini n f o r m a t i o n that should become increas ingly useful asregions develop and deta i led plans and environmentalassessments are needed.

R. B. M orrison, "Appl ica t ion of Skylab ERE P Photographs toS t ud y of the M odern Episode of Accelera ted Erosion in South ernA r i z o n a , " u n pu b l i shed F i n a l Repo r t , N A SA -U SG S A g reem en tT-4113-B, 1975.

FIGU RE 4-18.—A port ion of an S190B co lor- infrared photograp h of

th e Mount Etna Volcano in Sicily (SL3-87-355). Shades of red indi -ca te areas of vegeta t ion ; b lack areas show volcanic materia l from

previous erupt ions. >

1 6 4 S K Y L A B E R E P I N V E ST I GA T IO N S S U M M A R Y






33°00 'N

32 °45' N h

32c30'Nh

12-V. i/W i l lc o x P laya c

109°15'W




:

- ' • ' . .

(b)

F I G U R E 4-19.—Wil lcox Playa and Si lver City , Ar izona, a rea , (a) Eros ion-suscept ibi l i ty /ease-of -excavat ion map prepared from t he in t e rpr e t a -t ion of S190B photographs . Map uni ts are defined in table 4-IV. (b ) S190B color photograph of the W i l l co x Playa area (SL4-94-237).




T A B L E 4-1V.—Explanation of Map Units

M ap un i t Ease of excavation Erosion susceptibility Description

Easi ly excava ted an d r e a d i l y e r od i b le m a t e r i a l s

I b

E x ca va t i on e a sy ( l i g h tp o w e r e q u i p m e n t o r

h a nd t oo l s su i t a b l e

fo r e x c a v a t i o n )

E x ca va t i on e a sy

( l i gh t p o w e r

e q u i p m e n t o r

h a nd t oo l s su i t a b l e

fo r e x c a v a t i o n )

H i g h l y e r o d i b l e

G e ne r a l l y h i g h ly

e r od i b l e

U nconso l i d a t e d f i ne - t e x t u r e d a l l u -

v i um o n f lood p la ins an d l ow e r -

most s t ream terraces; mainly s i l t ,

some s a n d , l i t t l e or no gr a ve l ;

v ery li t t le or no so i l d e ve l op m e nt

U n c o n s o l i d a t e d s a n d y , sil ty to locally

c l a ye y , a nd s o m e w h a t g r a v e l l y a l-

l u v i u m of b a s i n - i n t e r io r l o w l a n d s

an d ba jada to e s lopes; soi l deve lop-

m e n t g e ne r a l l y n i l o r w e a k , l oca l ly

m od e r a t e

Ma t e r i a l s ge ne r a l l y e a s i ly e x ca va t e d ( l oca l ly m od e r a t e l y diff icu l t ) a nd ge ne r a l l y m od e r a t e l y e r od i b l e

E x ca va t i on ge ne r a l l ye a sy , l oca l l y m od -

e r a t e l y d i f f i c u l t

Erodib i l i ty m od e r a t e l yh i gh to m od e r a t e

Mos t l y s i l t y to p e bb l y s a nd y a l l u v i u mw i t h m o d e r a t e s o i l d e v e l o p m e n t

(clay a n d / o r c a r b o n a t e a c c u m u l a -

t i o n ) ; loca l pebble to cobb l e g r a v e l

w i t h m od e r a t e to no soi l deve lop-

m e n t

Ma t e r i a l s ge ne r a l l y m od e r a t e l y di f f i cu l t t o e x ca va t e a nd on l y s l igh t ly erod ible

E x ca va t i on m od e r a t e l y

d i f f i c u l t ( l i gh t o r

h e a v y p o w e r e q u i p m e n t

necessa ry fo r e x ca -

v a t i o n )

E ro d i b i l i t y m os t l y s l ight ,

locally m o d e r a t e

A l l u v i u m w i t h very s t rong soi l

d e v e l o p m e n t i n c l u d i n g s t ro n g

c a l c i u m ca r bona t e ( c a l i ch e ) a c -

c u m u l a t i o n a n d / o r moderate

i n d u r a t i o n below th e soi l prof i l e

a nd / o r coarse par t ic le s ize (cobble

an d bou l d e r g r a ve l )

Ma t e r i a l s m od e r a t e l y difficult o r di f f i cu l t to excavate an d genera l ly least e rod ible

Mo s t l y r ock e x c a va t i on ,

m o d e r a t e l y diff icu l t

to di f f i cu l t (h e a vy p ow e r

e q u i p m e n t needed fo r

e x c a v a t i o n ; r i p p i n g m a y

be necessary, a n d , in

places, b l a s t i ng )

Erodib i l i ty m os t l y ne g -

ligible, loca l ly s l igh t

to m od e r a t e

Consol ida ted bedrock is w i de l y

exposed; t h i n deposits o f gr a ve l l y

co l l uv i um or a l l u v i u m occur l oca l l y ,

w h i ch a r e c l a s s 2 o r 3 e x ca va t a b i l i t y /

erod ibi l i t y

168 S K Y L A B E R E P INVESTIGATIONS S U M M A R Y



W A T E R R E S O U R C E S

Surface -Wate r Management

One of the mos t s t r ik ing d i f fe rent i a t ions poss ib l efrom mu l t i spec t ra l ae r ia l a nd EREP sa te l l i t e imagery i s

t he ident i f i ca t ion and de l inea t ion of sur face -wa te rbodies . Accurate del ineat ion of regional drainage net -wor k s has been made poss ible by space photographs asdem onstra ted by Stoeckeler e t a l . ( ref . 4-34) , Colw el l e tal . (ref. 4-36), and Baker et al . (ref. 4-37). In instances inw h i c h overla p of the pho tographs enabled s tereoscopicv iewing , inves t igators were bet ter able to detect andcompare topographic rel ief . This capab i l i ty enabled th eaccurate del ineat ion of watershed boundaries by locat -ing the r idge l ines tha t c i rcumscr ibe i n d i v i d u a l surface-water drainage sys tems. For this purpose, th e S190B

pho tograph s were ne a r ly equa l to the bes t h igh -a l t i tude -aircraf t pho tographs ava i l ab le to the inves t iga tor ( f rom

an RC- 10 camera a t 18 300 m). This conclus ion is im-po r t a n t because frequent high- and low-al t i tude-aircraf t

coverage is expens ive . The demons t ra t ion of thecap ab i l i ty of the Skylab camera sys tems to p r ov i de ac -curate resolut ion o f dra inage basins and surface -wa te rbodies offers the poss ibi l i ty of s ignif ican t cos t savingswhen appl i ed on a na t ionwide or wor ldwide bas i s .

The Skylab mul t i spec t ra l photographic sys tem pro-vided coverage of the spectrum from the vis iblethrough th e near-infrared. Piech et al. (ref. 4-38) usedthese pho t og r a phs to assess th e va lue of r e m o te sensingfrom space for determining the eutrophicat ion of lakes .Compar i sons were m a d e be tween convent iona l wa te r -

qu a l i ty indices and rela t ive values of reflectance in theblue an d green po r t i ons of the vis ible spectrum a tvarious locat ions in Lake Erie , Lake Ontario, and Con-esus Lake, Ne w Yor k. Reflectances m easured from theS190A color photographs were in excel lent agreementwi th those de te rmined f rom s imul taneous a ircraf t

f l ights . Changes in the balance acquired on organic-c om pound c onc e n t r a t i ons of the surface waters causedvar ia t ions in the blue-to-green reflectance ratios. Therat io of blue-to-green reflectance in Lake Ontario is

shown in figure 4-21. Similar results were reported byHannah et a l . ( ref . 4-39) us ing data acquired over lakesin Florida . Because th e a t m os phe r e can reduce th emeasured reflecta nce by as mu ch as 60 perc ent , i t was

necessary to correct for this effect . Co rrect ion made byreference to reflectance s tandards w as used by Piech e t

al. (ref. 4-38) in t h i s succes s fu l appl i ca t ion . I t was pre-dicted that an addi t iona l advance in resolut ion wouldpe r m i t use of the s ha dow-c a l i b ra t i on p r oc e du re nowused in the measurement of eu t rophica t ion indices byl ow - f ly ing aircraf t . Th e synopt i c v iew provided b ysate l l i te ima ging sys tem s with repe t i t ive coveragewould enab le th e m oni t o r i ng o f na t u r a l a nd art i f ic ia l

lakes for the onse t or amel iora t ion of eut rophica t ion .Th e resolut ion of the Skylab camera sy s t e m s alsogreat ly fac i l i t a t ed th i s app l i ca t ion .

Yarge r and M cC auley (ref. 4-40) ach ieved goo dresul ts by ap ply ing the band -ra t io ing t echniqu e to theprob lem of detect ing the presence of suspended sol ids

in reservoirs. They found that reflectance values in bothS190A and S190B photographs correla ted well with sus-pended (mos t ly inorgan ic ) s ediment . Band ra t ios o fblue-green to red reflectances provided quant i ta t ive cor-rela t ion a t concentra t ions greater than 200 p/m in threesmal l reservoirs in Kansas . R epe t i t ive coverage pro-vided by satel l i tes could improve the regulat ion andm a na ge m e n t of lakes and reservoirs with respect to th i swate r -qua l i t y paramete r .

Snow Cover

An ever - increasing need in agr i cu l tura l , indu s t r i a l ,and met ropol i t an areas for rel iable sources of watermakes eff icien t m a na ge m e n t of water resources a con-t i nu ing concern . In many areas, wi n t e r storage of waterin the form of mounta in snow , toge the r w i th i t s runo ffregime, governs th e avai labi l i ty of wa te r dur ing th eper iods of greatest need. Because of the general inac-cessibil i ty of h igh-mounta in snowpacks and the i rrela t ively inhomogeneous d i s t r ibut ion a n d i r regula rboundaries , es t imation of tota l water content in them




Quar ry

Urban area

W a te r

. * Sioux Fa l l s

FIGURE 4-20.—Sioux Falls , South Dakota, area, (a ) Analytic-geomorphology m ap prepared from following S190B color photograph. Symbolsare d e f i n e d in table 4-V. (b ) S190B color photograp h (SL2-81-316).






TABLE 4-V.—Explanation of An alytic Geomorphology Maps of the Sioux Falls Study Area

(a ) Attributes identifiable on Skylab photographs

• • • •

2g

:-

:

hi

3c

4ce

4cl

W

-:

Landform characteristics Soil characteristics

Lan d-su rface Local relief, Stream dissection

form symbol mDensity Pattern

A l a , V, Vf <10 — Not

applicable

Ala, V, Vf <10 Low Not

app l icable

A t, Ala, Alb <20 — Not

app l icable

A l a , Alb , <30 Low Deranged

B l a , Bi b

B 2 b , Clb, C2b 15 to 30 Low Deranged

Clc, C2c 15 to 30 Low Deranged

Al a < 2 0 M e d iu m D e n d r i t i c

Clc, C2c < 30 M e d i u m T re l l i s

C3c, C3d, 30 to 60 M e d i u m T re l l i s

D2d, D 3d

C2c 20 to 45 High Pseudo-

rec tan-

gu la r

C2 d 20 to 45 Medium Deranged

C2d 20 to 45 High Pseudo-

rec tan-

gu la r

Interfluves

_

W id e , flat

V e r y wide.

i r r egu la r

topography

R o u n d e d

Fla t

Rounded

Some ro u n d e d .

some flat

M a n y Hat-

to p p e d ,

rounded edges

R o u n d e d

Some flat-

topped

ridges

Surface

color

D a r k

D ark

M e d i u m

D a r k

D a r k w i t h

l i gh t

mottle s

M e d i u m

w i t h l i gh t

mottle s

D a r k

D a r k tom e d i u m

M e d i u m to

l i gh t with

l ight

mottle s

L i g h t

M e d i u m

Very

light

M

drainage

Poor to

fair

Poor to

fair

Fair to

very good

Very poor

to fair

Very poor to

very good

Fair to

very good

Fair to

very good

Poor logood

Fair to

very good

Fair to

excel lent

Fair to

exce l len t

Fair to

exce l len t

Surficial-

geologic

deposits

Al l uvi a l c l ay , s i l t .

sand, and g rave l

Al l uvi a l sand an d

gravel, some s i l t

Al l uvi a l sand an d

gravel, some silt

Ground moraine ;

clayey t i l l -

unsorted clay , s i l t .

sand, grave) , an d

boulders

Stagnation m o ra in e :

clayey t i l l -

unsorted c lay , silt.

sand, g rav e l , and

boulders

En d m o ra in e ;

unsorted clay , silt.

s and, g rave l , and

boulders

Loess, c o m m o n l y

severa l mete rs t h i c k .

over somewhat-

leached t i l l l ike

above

Unsorted clay , s i l t .grave l , an d boulders

Unsorted clay , s i l t .

s and, g rave l , and

bou lde rs


severa l m e te r s t h i c k .

over weathe red an d

leached c layey t i l l


several meters t h i c k .

over weathe red an d

leached clayey t i l l

Loess, commonly

severa l mete rs th ick .

ove r weathe r ed and

leached clayey t i l l

Special problems

or attributes

C o m m o n l y subject to f loodi

near s treams ; high wa te r

tab le in m a n y places

C o m m o n l y sub jec t to floodi

near streams; high wate r

table in many places

None

Poorly drained depres s ions

places

Poor ly draine d depres s ions

in places

None

N o n e

N o n e

N o n e

N o n e

N o n e

None

i

1 7 2 S K Y L A B E R E P I N V E S T I G A T IO N S S U M M A R Y



T A B L E 4- V.— Cont inued

(a ) Con t inued

Y o u n g valley lowlands - flood plains an d lower s tream le rraces of Holocene

and in p laces o f W iscons inan age

Glac ia l outwash te rraces , channe ls , an d p l a in s of late W iscons inan

age

Stream te rraces , main ly o f Wiscons inan age

G ro u n d m o ra in e of late W iscons inan age; nearly level to gen tly

r o l l i ng pla ins ; some poorly drain ed depres s ions, marshes , ponds ,

and lakes

Stagna t ion moraines of late Wisc ons inan age ; gen tly roll ing plains ;

m a n y poorly drained depres s ions , marshes , ponds , and lakes

En d moraines of late W isconsinan age; lo w r idges , mos tly gen tly

sloping, in places d is con tinuous

G e n t l y rol l ing dr ift pla in of early Wiscons inan ag e covered with late

W i s c o n s in a n loess; d ra in ag e generally well in tegrated

Topograph ica l ly s imi la r to I l l ino ian dr i f t plain (4cl) bu t m u c h d a rk e r

toned and slightly subdued relief

Highes t end moraines o f late Wiscons inan age (su rrounding Turkey

Ridge)

l l i n o i a n dr i f t pla in ; w e a th e re d clayey t i l l m an t l e d genera l ly wi th

severa l meters of late W is c o n s in an loess; well-dissected

u p l a n d p l a i n

has been diff icul t . Hoffer (ref . 4-23) demonstra ted thatphotographs f rom the S190A camera and imagery f romthe S I92 scanner have p otent i a l use in de l inea t ing snowcover (fig . 4-22). A s imple d e l inea tion of snow-coveredareas u su a l ly is not poss ible because of obscurat ion byclouds , vegetat ion canopies , or shadows of clouds .

How ever, digi ta l process ing of the SI92 imagery dataenabled recogni t ion of five spectra l classes of snow-covered areas ( table 4-VI) according to differences inth e p r opo r t i on of the forest or vege ta t ion canopy con-s t i tu t in g each p ic ture e l ement (p ixe l ) of the scannerdata . Computer process ing of the da ta pe rmi t t ed th edig ita l over l ay of 13 bands of E RE P d a ta , 4 bands ofLandsat multispectra l imagery, and topographic data( i nc l ud ing elevat ion, s lope, and aspect) . Th e ca pa b i l i ty

of compar ing mul t ip l e da ta sets provides an effect ivem e a ns for rap id ly genera t ing accura te snow-cover mapsusing the repet i t ive coverage that wil l be provided byfuture satellites.

Acc ording to Barnes et a l . ( ref . 4-41) , the differe nt ia-t ion of cloud cover from snow cover can be ac-complished by selective use and analys is of SI92 imag-ery data. Snow reflectance is h igh in the vis ible part ofth e electromagnet ic spectrum bu t drops to com-

para t ive l y lo w levels in the 1.55- to 1.75-^.m an d 2.10- to2.35-^m bands . In the imagery covering this range(SI92 bands 11 and 12) , snow ap pears to be nearly blackregardless of age and condi t ion , but wa te r and c loud- top

reflectances are un ifor m ly high througho ut the range.Through computer process ing of the data , a clear dis-t inct ion can be m a d e between cloud tops and snowcover. A n area showing a high reflectance in the visible

range but a low reflectance in the nea r - inf ra red range( S 1 9 2 band 11 or 12) can be recognized as sno w; an areashowing high reflectance in both spectra l regions can berecognized as water or clouds . Most snow-free areas ex-h ib i t rela t ive ly low reflectances in the vis ib le range an dmed ium reflectance in the near-infrared range (f ig.4-23) . Exploi ta t ion of this technique for automaticsnow-cover recogni t ion and m a p p i n g w as s h o w n to beposs ible; when fully deve loped , i t may aid in bettermanagement of large watersheds for f lood protect ionand maximum wate r s torage and ut i l i za t ion .

Hydrological Factors

The hydrological factors discussed are f lood predic-t i on , wa t e r s he d m a na ge m e n t , a n d a nc i e n t wa t e rsys tems.




T A B L E 4- V.— Cont inued

(a ) C ont inued

' ' / .

Land-surface

form symbol

7a Blc, Cld, Die.

Did, Di e

7b C2d. D2c.

D2d, D 2e

7c D3c, D3d,

D3e. D4 e

C2c. C2d

L andfor m characteristics Soil characteristics

Local relief. Stream dissection Surface

Dens i t y Pattern Interfluves

<3 0 Very Semi- Few to no Dark

high par- gently

(gullied) a l l e l sloping

interfluves

30 to 60 Very Semi- Few to no Medium

high par- gently

(gul l ied ) allel sloping

interfluves

>6 0 Very Semi- Few to no Medium

high par- gently

(gullied) allel sloping

i n t e r f l u v e s

15 to 45 Low Radial Medium to

l i g h t

Mdrainage

E x c e l l e n t

Excellent

Exce l len t

Excellent

Surficial-

geologic

deposits

Variable

Variab le ; commonly

l i k e 4cl. bedrock

exposed locally

Variable; commonly

like 4cl; bedrock

exposed locally

Kam e - sand, grave l ,

boulders

Special problems

or attributes

None

None

None

Good source of sand

an d grave l

(b) Environmenta l -geomorphic /geological limitation^

Map Topographic

units l imitat ions

1 3

lo

It 3

2g

2s 2,3

2e 2,3

2m 3

3c 2

fee

4d \2

4d 1,2

4dl U

7t

7b

7c

8 1

Shallow ground Gravel Rock

water availability availability! availability/

quality Quali ty

2.3 1

3 1

3 3

UJ U

1.2.3 1,2 1

1,2.3 U 1

1.2,3 1.2 1

2 2

U IJ

U 1 1

U 1 1

U 1 1

1 1 1

1

1

3 3

Slope stability

!

:

:!

:

:

:

:

:

2

:

1

-

U

Construction

Foundations

: \: : ;

U,3

UJ

:

2^

2J

2J

:

1

:

2J

Ease of Roads

excavation

3

3

3 33 3

3

3 2,3

3 3

3 2

3

3 23

2,3

3 2,3

IA 3

U.3 1

3

al is severe, 2 is moderate, and 3 is few.

1 7 4 S K Y L A B E R E P IN V E S T I G A T I O N S S U M M A R Y



T A B L E 4-V.— C onc luded

(a ) C onc luded

Remar ks

Bluf f s ; u n i t s 7b and 7c g e n e r a l l y have , a t t op , severa l m e t e r s of loess

over weather ed c l ayey t i l l of I l l in o ia n ag e o v e r Sioux Quar t z i l e

(exposed local ly)

Gl ac i a l k a m e s ( g r a v e l l y h i l l s )

(b ) Concluded3

Drainage

Surface Soil

(internal)

1,2 1,2

3 3

3 3\2 1 .2

1.2,3 1,2

3 1,2

2,3 1,2

3 U

3 1,2

3 1,2

3 1,2

3 1,2

3 2,3

3 2,3

3 2.3

3 3

Erodibility

1 ,2

2,3

2,3

2,3

2,3

1, 2

2,3

2

1,2

u1,2

1J

1

1

1

2

Waste disposal

Sanitary

landfills

1.2,3

u

1, 22.3

2,3

2,3

2,3

2,3

2,3

2

2

2

2

2

2

1

Sewage

lagoons

1.2,3

U

1, 22,3

2,3

2,3

2.3

2,3

2 , 3

2

2

2

2

2

2

1

Septic

tanks

1.2,3

3

3

1.2

1,2

1,2

1,2

1.2

1,2

2,3

2,3

2,3

2

2

1

3

1 is severe. 2 is moderate, and 3 is few.

Flood predic t ion.—Flood-hazard indices ar e of tenused by insurance companies , banks , and others con-cerned wi th eva l ua t ing i n v e s t m e n t r i sk . M u l t i s p ec t r a lpho tograph s a r e usefu l in de f in ing r e la t ionsh ip s be-tween th e loca l geomorpho logy and land use w i t h i n agiven watershed. For example, in central Texas, w h er eth e orograph ic inf luence of the B a l c on es E s c a r p m e n tt ends to local ize thu nde rstorm s, it has been suggestedby Baker et al. (ref. 4-37) that local geomorphology ofth e several draina ge basins governs th e conver s ion ofstorm pre cip i tat io n to f loods. A test of thi s idea and thebeg inn ing of the d evelopment o f a quan t i ta t ive hy -d rogeomorph ic model to describe th e f loods ar e m a d epossible by the avai labi l i ty of repeti t ive s atel l i te imag-ery . A s imi la r app l ica t ion was m a d e by Colwel l et al.(ref. 4-36) in def in in g pa t te rns of r u n o f f and a l luv ia t ionin the San Bernard ino Mounta ins . Geohydro log ica lun i t s w i t h i n drainag e basins were easi ly recognized anddel ineated by r idge l ines , drainage divides, faul ts , andc o n t a c t b e t w e e n d i f f e r e n t l i t h o l o g i c a l u n i t s . A

general ized model of ground water movement was con-structed that inc ludes a predic t ion of f lood hazards inth e sou th -cen t r a l Mojave Desert . This model can bevery useful in p l a n n i n g for the order ly g rowth anddevelopment of rapidly ex p a n d i n g c o m m u n i t ie s in th i sregion. Th e S190B photog raph s br idged the gap betweenhigh-al t i tude aer ial pho tograph s and relat ively low -reso lu t ion mul t i spec t r a l imagery . Similar resul ts wereobtained at s tudy si tes in I l l ino is , Iowa, Kansas,Missour i , Nebraska , an d South Dakota (ref. 4-9).

Watershed management.—A detai led compar ison ofSkylab S190A and S190B ph otogra phs and high -al t i tud e-aircraf t pho tographs o f the New England a rea was

mad e by Cooper et al. (ref. 4-42) to provi de hyd rolog icalinformat ion needed fo r reservoir management. Therelat ionship between the land use wi th in a water shedand its hydrological characteristics is generally believedto be f u n d a m en t a l to an under s tand ing of water shedfunct ioning. Th e ER EP S190B pho tographs made possi -b le the identif ic at ion and d el ineation of al l 6 Level Iclassification units (ref. 4-43), 17 Level II units , and 1Level II I unit. (See table 2-1 in sec. 2. ) These results ar ea lmos t as good as those obtained with th e best high-

al t i tude-aircraft pho tograp hs (6 Level 1 ,21 Level I I, and5 Level II I un i t s ) ; at L ev e l II , they are practical ly equalin uti l i ty . The S190B pho tographs mee t th e remote-

sensing requiremen ts for regional land use map pin g andfo r eva lua t ion of runof f potentials in s i tua t ions r equ i r -in g regional hydrologica l surveys for urban p lan ning or






F IGUR E 4-22.—San Juan Mountains in southwestern Colorado, (a) S190A color photograph, showing the extent of snow cover (SL2-10-016).Outl ined area is sho wn in f igure 4-22(b) . (b) Area out l ined in f igure 4-22(a). (c) Color-coded snow classification map of S192 digi ta l data inw h i c h five spect ral classes of snow have been separated. Th e data can be used to determine th e area! extent of the snowpack.

GEOLOGY A N D H Y D R O L O G Y 1 7 7



FIGURE 4-23 .—S192 data acquired over th e W hi t e M o u n t a i n s a rea

in Cal i fornia on J u n e 3, 1973 (ref. 4-41). (a ) Visib le band 3 (0.52 to0.56 /urn) , (b ) N ea r - i n f ra red b a n d 11 (1.55 to 1.75 M m ) - Th e cha n g ein the background reflectance for snow makes the clouds easier toident i fy .

resource deve lop ment . S im i l a r resu lt s were repo r ted byStoeckeler et al. (ref. 4-34).

Anc ien t water systems.—Skylab ph otog raph s enabledG um e r m a n et al. (ref. 4-44) to s t udy th e hy d r o l ogy ofprehi s tor i c fa rming sys tems wi th in a la rge and envi ron-mental ly diverse area of cent ra l Ar izona . Hyd rologi s t s ,geologists, biologists, and archeologis ts evaluated th eadapta t ion of prehi s tor i c man to the semia r id desert ofcent ra l Ar izona and h is creat ion of l a nd m a na ge m e n tand water con trol sys tems. Ecolog ical ly s ignif icantsubareas , or drainage basins, were selected on the basisof basin area, stream length and order , s lopes , bedrocktype, and ra infal l dis t r ibut ion. Table 4-VII i l l us t ra tes

th e usefulness of S190A and S190B photographs fo rd e f i n i n g e n v i r o n m e n t a l p a r a m e t e r s . E s t i m a t e s o f

avai lable water were es tabl ished from these parametersand f rom vege ta t ion communi t i es , and an eva lua t ion o ftypes of prehi s tor i c wa te r management sys tems w asbased on these data .

i nS c a l e , k m

T A B L E 4-VL —S now packA rea W ithin 100-mElevation Increments for the FiveSpectral Classes of Snow Cover

Elevat i on ,

m

Above 3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

t o 3700

t o 3600

t o 3500

t o 3400

t o 3300

t o 3200

t o 3100

t o 3000

t o 2900

t o 2800

t o 2700Below 2600

Snowpack a r e a , hm , for

s p e c t r a l c l as s —

I

1 1 7 9

400

1 2 9

45

1 3

7

60

0

00

00

2

2464

1 9 1 4

1 8 6 8

904

378

94

22

6

1

0

0

0

0

3

308

694

1 8 5 8

1 8 5 8

1305

922

529

2 1 3

3 8

4

1

0

0

4

10 8

1 3 5

5 1 7

1266

1 4 1 7

1 2 5 8

793

433

188

54

1 3

1

0

5

1

3 7

6 1

280

8 1 2

1 2 9 8

1 5 4 0

1 0 41

5 3 5

289

1 4 7

9 579

T o t a l a r e a ,

h m

4

3

4

4

3

3

2

1

066

180

433

353

925

579

B90

693

762

347

16 1

9679

T o t a l s 1 7 7 9 7651 7730 6183 6221 29 564

1 7 8 S K Y L A B E R E P I N V E S TI GA T IO N S S U M M A R Y



TABLE 4- VII.—Evaluation of the Usefulness 0/S190A andS190B Photographsfo r Interpreting

E nvi ronmenta l Features of Interest to Regional Archeological Studies

Features studied

Black an d

white

Color

S190A

Color

infrared

Enhanced

color

Color

S190B

Color

infrared

T op ograp h i ca l

Marinade:

Ha bi t a t i onR o a d w a y s

N a t u r a l :Ma j or d r a i na ge -

w a y sM i n o r d r a i n a g e-

way sPlains a n d bajadas

Hil ls , buttes, a n dmesas

M o u n t a i n s

PoorPoor

Fair

Poor

Good

Good

Good

FairFair to poor

V e r y good

V e r y good

V e r y good

V e r y good

V e r y good

Poor

Poor

Good

Good

Good

Good

Good

Good

Good

V e r y good

Good

Good

Good

Good

Good

V e r y good

V e r y good

V e r y good

V e r y good

V e r y good

V e r y good

Good

Good

V e r y good

V e r y good

V e r y good

V e r y good

V e r y good

Vegetational

R eg i o n a l :V e ge t a t i on types

G e n e r a l d e ns i t ypatterns

R i p a r i a nN o n r i p a r i a n

Local:Di f fe r e nce s i n

ve ge t a t i on den-

sities on

s lopes ofd i f f e r e n t e x -posures

Di f fe r e nce s i nve ge t a t i on den-

sities on

l o wer / h ig he rpo r t io n s o fslopes above

l arger d r a i n a g e sDi f fe r e nce s in

ve ge t a t i on den-

s i t ies in d ra in-ag e channels

as a func t i onof a d j a ce n tslopes

W i d t h of r i pa r i anve ge t a t i onz o n es i n m a j o rdr a in ag es

A g r i c u l t u r a l

Poor

Poor

Fa i r

F ai r3

Fai r

Poor

Poor

Poor

Poor

PoorFair

Fair3

Fai r

Poor

Fair

Poor

Poor

Poor

Fai r

Fair3

Fai r

Poor

Poor

Fa i r

Poor

Poor

Fair

Fai r

Fair

Poor

Poor

Poor

Poor

F a i rFa i r

Fair

F a i r

F a i r to poorb

Fai r

Good

Fair

Good

Good

Good to fa i rb

Good to fa i rb

Good to fairb

Good

V e r y good

General r a t i ng

T o p o g r a p h yV e ge t a t i on

FairPoor

Good

PoorFairPoor

Good

PoorV e r y good

Fa i rV e r y good

Good

Diff i cul t i es caused by shadows- Some areas bet ter t h a n othe rs .




F I G U R E 4 -2 4 .—South-c en t r a l Mojave Deser t in Ca l i fo rn i a , (a ) S190B color photograph (SL4-92-349). (b ) Ge oh yd ro log i ca l m ap based on in-

t e rp re t a t i o n of Skyla b photographs .

Ground Water

The locat ion of rel iable sources and suppl ies ofground water is of growing socia l and economic impor-tance in nearly all parts of the world . It has become ob-vious that ground water exis ts in l imited quant i t ies andt h a t th e c o n t i n u e d e x i s t e n c e o f t h e s e q u a n t i t i e s

u l t imate l y de pe nds on the rate of rep leni shment . Forra t iona l resource management , i t i s impor tant to haveth e m e a ns ava i l ab le fo r l oca t ing ground wa te r reserves.

A l t h o u g h aerial and satel l i te imagery can provide onlyindi rect evidence of ground water reserves , this evi -dence can be accurate and defini t ive under some cir-cums tances .

Skylab photographs and imagery are useful for theassessment of ground wa te r resources, both in t e rms ofspa t i a l d i s t r ibut ion and of func t ioning . According to

Colwell et al . (ref. 4-36), arid lands such as the south-centra l M ojave Desert are most amen able to analys is bypho to in t e rp re t a t i ve t echniques , and the informat ion






rVaWWF*t?

^Hm>.tf - r

n d i o H i l l s

F IGURE 4 - 2 5 . —Ind i o H i l l s an d C oac he l l a V a l le y jus t nor t h of the Sal ton Sea in southern Cali fornia, (a ) Enlarged port ion of S190B photograph

(SL4-92-3S1) . (b ) A i r c r a f t v iew of the B anni ng F au l t in the nor t h e rn Coach e l l a V a l le y . The flow of ground w at e r has been blocked by i m p e r -vi ous m at e r i a l on the left side of the f au l t , c aus i ng a h i gh g round w at e r table an d vegetat ion growth on the right side of the fault .

generated could be of immediate u t i l i ty in manag ing thewater resources of these regions. Geohydrological unitsare del ineated by noting such flow barr iers as drainagedivides, faul ts , and l i tho logica l contacts , wh ich areeasi ly discernible on photographs (figs. 4-24 and 4-25).Lithological units are d i s t i n g u i s h a b l e and their per-meabi l i ty may be deduced f rom l i thology. From s tudyof E R E P p h o t og r a p h s, a general ized model fo r groundwater movement wi th i n the sou th -c en t r a l Mojave

Deser t w as postulated by ou tl inin g the drainage basins ,del ineat ing the i nd ivid ual geohydrological and l ithologi-cal units , and dedu cing the hyd rological charac ter is t icsof the l i thological units .

W ater-well siting on lineaments.—In ce ntral Ten-

nessee, ground water occurs mostly in a n e t w o r k ofsolution cavit ies . I t seemed reasonable that the l inea-me nts vis ib le in the Skylab photog raphs migh t show theexistence and location of a major s tructural system of




FIGURE 4-25.—Concluded .

joints that interconnects this system of cavit ies andgoverns th e rate at which this ground water can beremoved. Acc ordingly , Moore (ref . 4-45) s tudied thel ineament types revealed by the view from space. Hethen co mpiled data on w ater y ields f rom w ells in thisarea and separated the values of those located on linea-ments vis ib le in the Skylab pho tographs f rom al l theothers. He found that the yield of water wells located onthese l ineaments w as approxim ate ly s ix t imes tha t o fr a ndom l y located wells (table 4-VIII). I t was concludedthat when w ater -w ell y ields of 1.6 X 10 ~

3mVsec (25

gal /min) are required, large savings in time and moneycan be achieved by locating th e wells on l ineamentsmap ped by stereoscopic view ing of Skylab photograph s.

For w ells ha vin g yields larger than 6.3 X 10 ~ 3 mVsec(100 gal /min), the potential cost saving between wellsr a ndom l y located and those on or near stereoscopic andproject ion l inears is ap prox ima tely $18 000.

Near-surface ground water.—In s o me areas , th e pres-ence of near -surface groun d water is c lear ly , al thoughind i rec t ly , ind ica ted by tonal or t ex tu ra l var ia t ions inspace pho tographs . These var ia t ions may be caused bydifferences in surface vegetation, soil composition, orsome s imi la r factor (ref. 4-2). Near-surface groundwater may r epresen t an impor tan t un tapped g roundwater resource in some places or an und esirable bui ldu pof the water ta ble as a consequence of excessive irr iga-

t ion or poor drainage in others . When combined w i t h aprogram of ground-based measurements , analysis of theS190B-quality photographs permi t s th e identificationand del ineation of some types of near -surface groundwater wi th a degree of precision fa r greater than that

possible f rom conventional ground-survey methodsalone (Bannert et al., ref. 4-46; fig. 4-26).






Isolines of depth to ground water in meters

Depth to g round water less than 2 . 5 m

Depth to ground water more than 10 m

Scale, km10

F IGUR E 4-26.—Concluded.




TABLE 4- VIII.—Comparison of Results of Random Drilling With

Locat ions on or Near Lineaments

Location of wells N o. of wells necessary to obtain yield, m '/sec (gal/min). larger than—

0.63 X 10 ' (10) 1.6 X 10 ' (25) 3.2 X 10 ' (50) 6.3 X 10 (100)

R a n d o m l y located

On or near S ky lab l inea men ts :Stereoscopic l ineam entsProjection l i n e a m e n t sEi t he r stereoscopic or project ion

l i neament sStereoscopic and projection

l i neament s3

Between Skylab l i n e a m e n t s

On o r nea r La ndsa t l inea m en ts

On or near aeria l pho tograph

l i neament s

: -

•

: I-

•

-

;4

1 1

5

- -• :

14

• • •

4

2 0

17

5 0

4 ;

41

L i n e a m e n t s delected both by s t e r e o v ie w in gand by pro jec t ion .

S U M M A R Y

S kylab E RE P da ta p rovide the geologi st w i th an idealc o m b i n a t i o n o f s t e r e os c op i c s y n op t i c v i e w a n dmul t i spec t ra l coverage of his area of interes t . This broadview c an reveal reg iona l pa t t e rn s of geology , l andform s ,and dra inage tha t are not as obvious on large-scalephotographs . The a va i l a b i l i ty of a varie ty of images for

a given area a l low s an inve st igator to f ind the bes t imageor com bina t ion of images for s tudy of h i s pa r t i cu la rr e g io n . A l t h o u g h S 1 9 0B c o lo r p h o t o g r a p h s w i t hstereoscopic coverage and high reso lu t ion proved to beth e mos t pre fe r red produc t , a ll produc t s were found tobe useful to some ex tent , depending on geology, vegeta-t ion , topography , an d season. Analys i s of the E R E Pdata led to a num ber of geological ly s ignif icant resul ts .

1. P ho t oge o l og i c a l r e c onna i s s a nc e a nd r e g i ona lm a ps as good as or bet ter than publ ished smal l -scalem a p s can be rap id ly prepa red .

2. Detai led geological maps were m a d e for arid orsemiar id regions for use in c on j unc t i on w i t h pub l i s he dda ta and g r ound c he c k i ng .

3. In more heavi ly vegetated areas, the general s t ruc-ture, par t i cu la r ly l ineaments and large folds, was in -fe r red through topographic and dra inage ana lys i s .

4 . M a ny p r e v i ous l y unk nown s t r uc t u r e s we r e d i s -

covered that were verif ied by f ie ld checking.5 . Act ive fau l ts and other evidence of recent ground

mov ement were loca ted .6. Areas w ere targeted for specialized large-scale

ground surveys of va r ious k inds . For examp le , maps ofl inear pat terns and in ten si ty , wh ere rela ted to rock frac-

t u r ing , have s igni f i cance in minera l resource , groundwate r , and engineer ing appl i ca t ions .

7. Surface -wa te r and snow-cover inv entor ies weres h o w n to be feasible.8 . Cons iderab le reduc t ion in costs of explora t ion

w as doc um e n t e d .Th e E R E P s t ud i e s led to the de ve l opm e n t of new

models or hypotheses , or to refinements or re ject ion ofolder ideas , which in turn led to a reappraisal of areasf o r m e r l y c ons i de r e d de vo i d o f e c o n o m i c m i n e r a ldeposi ts . Th e geological invest ig at ions and app l icat ion sdescribed in this sect ion are the begin ning of the use ofE R E P data . Researchers associa ted with th e exper i -m e n t s will ex tend the i r app l i ca t ions to o the r geographi -cal areas, and new users wil l have the opp or tun i ty to useE R E P d a t a in their part icular areas o f interes t . A sf u tu r e space pla tforms are des igned and b e c om e opera-t i ona l , th e lessons l ea rned and the meth ods te s ted du r -in g th e E R E P p r o g r am w i l l c on t r i b u t e to a be t te r und er -s t anding of the d i s t r i b u t i on of the Ea r th ' s resources.




R E F E R E N C E S

4-1. Quade , Jack G .; T re x le r , D. T. ; e t al . : Geologic Inve st igat io n

in t h e B as in and Range of Ne vad a U s i ng S ky lab / E R E P

Data. NASA CR-144497 , 1975.

4-2. L e e , Ke e nan ; H ut ch i ns on , R. M. ; e t al. : Geologic and

M i n e r a l and W at e r Re s ource s Inve s t i ga ti ons in We s t e rnC olorado , U s i n g S k y l a b E R E P D a t a. N A S A C R - 1 3 8 7 2 2 ,

1974.

4-3. W i l l i am s, P . L . : Geology, S t ructu re , and Ur an ium D eposit s

o f th e M oab Q uad ran g le , Co lo rad o and U t a h . U .S . Geol.S u r v . Misc. Geol. Inv. Map 1-360, 1964.

4-4. Hoppin, R . A. ; Caldwell , J . ; et al . : Experiment To Evaluate

th e Feasibi l i ty of Uti l i z ing S k y l a b - E R E P R e m o t e S e n si n g

Data for Tectonic A nal ys i s Throug h a Stu dy of the Big Horn

M o u n t a i n Re gi on , W yom i n g . NA S A CR- 1 4 7 5 4 3 , 19 76 .

4-5. H ous t on , R . S . ; M a r r s , R . W . ; and B orgm a n , L . E . :

Mul t i d i s c i p l i na r y S t ud y of W yom i ng T es t S i te s . NAS A

CR- 1 4 7 7 1 9 , 1975.

4-6. Lambert , B . P . ; B e ns on , C. J. ; et al.: A S t ud y of the Useful -

ness of S ky lab E R E P D at a fo r E ar t h Re s ources S t ud i e s i n

A us t r a l i a . NASA CR-144493, 1975.

4-7 . S toiber, Ric ha rd E. ; and Rose, W i l li a m I . : An I nve s t i ga t i on

o f T h e r m a l A n o m a l i e s in the Ce nt ra l A m e r i can V olcan i c

C h a i n an d E valua t i on of the U t i l i t y o f T h e r m a l A n o m a l y

Mo n i to r in g in the Pred ic t ion o f V olcan i c E rup t i ons . NAS A

CR-144496, 1975.

4 - 8 . V a n d e r M e e r M o h r , H. E. C.; and S r i vas t ava , G. S. : E v a l u a -

t i on o f E R E P T e ch n i q ue s fo r Ge o log ica l M ap p i ng : S u m m ary

Statements . N A SA CR-144494, 1975.

4-9. Morri son, R. B . ; Lineback, J . A. ; e t al . : Applicat ions of

S ky l a b E R E P P h o t o g r a ph s t o M a p p i n g L a n d f o r m s a n d E n -

v i r o n m e n t a l Ge om orp h o logy i n t h e Grea t Pla i ns and M i d -

west . NASA CR-144491 , 1975.

4-10. Olson, Norm an K. : Ap p l i c a t i on o f M ul t i s p e c t r a l Ph o t ogra -

phy t o M i ne ra l and L and R e s ource s o f S ou t h Caro l i na .

NASA CR-144109, 1975.

4-11. Cassini s , R .; Lech i , G. M. ; and Tonell i , A . M . : Result s of

Sk y lab Invest igat ion Over I t aly . NASA CR-147396, 1975.

4-12. M eri f ie ld , Paul M . ; and L am ar, D. L . : Fault Tectonics and

E ar t h q uake H azard s i n Par t s o f S ou t h e rn C a l i fo rn i a . NA S A

CR-144477, 1976.

4-13. Collins, R. J.; Petzel, G. J . ; and Evere t t , J . R. : E valua t i on o f

th e Sui tabi l i ty of Skylab Data for the Purpose of Pe t roleum

Exp lo r a t io n . NA S A CR- 1 4 7 4 6 8 , 1 9 75 .

4 - 1 4 . M c M u r t r y , George J . ; and Pe t e r s e n , Gary W . : In t e rd i s c i p l i n -

ar y A p p l i c a t i o n s a n d I n t e r p r e t a t i o n s o f E R E P D a t a W i t h in

th e S u s q u e h a n n a R i v e r B as i n . NAS A CR- 1 4 7 5 4 1 , 19 7 6.

4 -1 5 . Abd e l - Gaw a d , M o ne m ; and Tubbe s i ng , L i nd a : Ana ly s i s o f

Tectonic Features in U.S . Southwest From S kyl ab Photo-

graphs . NASA CR-144464, 1975.

4 - 16 . Je ns e n , M e ad L e R oy ; and L a y l a n d e r , Phi l ip : S u m m a r y ofS p ace Im age ry S t ud i e s i n U t ah and Ne vad a . NAS A E ar t h

Re s ource s S urve y S ym p os i um . NA S A T M X- 5 8 1 6 8 , vo l . IB ,

1975, pp. 673-712.

4-17. Bechtold, Ira C. ; Re yno ld s , J. T.; A r c h e r , R. L . ; and W a g n er ,

C . G . : An E va lua t i on o f S ky lab (E R E P) R e m ot e S e ns i ng

T e c h n i q u e s A p p l i e d to Inve s t i ga t i ons o f Crus t a l S t ruc t u re .

N A S A CR-147458, 1975.

4-18. Goetz, A. F. H. ; A b r a m s , M. J . ; e t al . : Compari son of S ky lab

an d L A N D S A T I m a g e s fo r Ge olog i c M ap p i ng in N o r t h e r n

A r i z o n a . NASA CR-147503, 1976 .

4-19. Lee, K.; and Rai ne s , G. L. : An E v a l u a t i o n of M u l t i b a n d

P ho to g r aphy f o r Rock D i s c r i m i na t i on . P roce e d ings of theT h i rd Confe re nce o n Earth Resources Observat ion a n dAnalys i s S ys t e m s (T u l lah om a, Tenn . ) , vol. 3, 1974, pp.

361-396.

4-20. T h o m s o n , F. : M a ch i ne P roces s ing of S-192 and S u p p o r t i n g

A i r c r a f t Data: S tud ies of At m os p h e r i c E f f e c t s , A g r i c u l t u r a l

C las s i f i c a t io n s , a n d L a n d R e s o u rc e M a p p i n g . N A S A

CR-144503, 1975.

4-21. Ch ang , D av i d T . ; and I s aac s , Rona ld G . : E x p e r i m e nt a l

E v a l u a t i o n o f A t m o s p h e r i c E f f ec t s on R a d i o m e t r i c

M e a s u r e m e n t s U s i n g t h e E R E P o f S k y l a b . N A S A

CR-144500, 1975.

4-22. Jero me, J. E.: Some Features Pert inent in Explorat ion of

P o r p h y r y Co ppe r Deposits. Geology of the P o r p h y r y C o p p e rD e p os i t s , S ou t h w e s t e rn Nor t h Am e r i ca , S. R. Ti t ley a n d C .L . Hicks , eds . , Univ. Arizona Press, 1966, pp . 75-85.

4-23. Ho ffer, Roger M .: C o m p u t e r - A i d e d A n a l y s i s of S k y l a b

Mu l t i s pec t r a l Scanner Data in M ount a i nous T e r ra i n fo r

L and Us e , F ore s t ry , W at e r Re s ource , and Ge o log ic Ap p l i c a -

t ions . NASA CR-147473, 1975.

4-24. Watson, K .; O'Leary, D. W . ; a n d P o h n , H. A.: A Photo-

geologic Com p ar i s on of S ky lab and L and s a t Im age s o f

S ou t h w e s t e rn N e vad a and S ou th e as te rn Ca l i fo rn i a . NA S A

CR-144642, 1975.

4-25. C ar l s on , J . E. ; and M a b e y , D. R . : Grav i t y an d A e r o m a g n e t i c

M a p s o f th e E ly Are a , Wh i t e P i ne Count y , Ne vad a . U .S .

Geol. Surv. Geophys . Inv. M ap GP-392, 1963.

4-26. Hose, R. K. ; and Blake , C ., Jr . : P re l im ina ry Geologic M a p o f

W h i t e P i ne Count y , Ne vad a . U . S . Geol. Surv., 1970.




4-27 . A ms bu ry , Da vid L. ; Cla nton , Uel S . ; and Frie rson, Von R. : 4 -37 .

Small-Scale Imagery: A Us e fu l Tool fo r M ap p i n g Ge o log i ca l

Features in the Texas Gulf Coastal Pla in. N A S A E a r t h

Resources Survey Symp osium , NA SA TM X-58168 , vol . IB ,

1975, pp. 833-849.

4-28 . Gui l lem ot , J . : Project Pyr alp : Tectonic Rel at ion sh ip Between 4-38 .

Pyre ne e s and A lp s (S ou t h e rn France). N A S A C R - 1 4 01 2 7,

1974.

4-29 . Vargas F . , Carlos : Inte rpre tac io n Geologico-Fis iograf ica de

Una Fotograf ia Sky lab Co rrespo ndien te al Area: Santa Cruz - 4-39.

M o n t e r o - B u e n a Vista. Yacimientos Pe t roleferos F iscales

Bolivianos , Special Repo rt , 1975.

4-40.

4-30. Austin, C. F. ; A u s t i n , W . H . , J r . ; a nd L e onard , G . W . :

Geothermal Science a nd T e ch no logy—A Nat i ona l P rogram .

U.S. N a v a l W e a p o ns Center Tech. Ser. 45-029-72, 197 1. 4-41.

4-31. Duff i e l d , W . A . : L at e Ce nozo ic Ri ng F au l t i ng an d Volca-

nism in the Coso Range Are a o f Ca l i fo r n i a . Geology, vol. 3,

no. 6, 1975, pp. 335-338. 4-42.

4-32. Anderson, D. H.; and H al l , R. A. ; eds.: G eo t he rm a l Ex-p l o r a t i o n i n t h e F i r s t Q u a r t e r - C e n t u r y . G e o t h e r m a l

Resou rces C ou nc il Special Re po rt No . 3, 1973, pp. 117-144. 4-43.

4-33. S iegal , Ba rry S . ; Ka hle , Ann e B. ; e t al . : The Detect ion of

Ge ot h e rm al Are as From S ky la b T h e rm al D a t a . NAS A

C R - 1 4 3 1 3 3 , 1975. 4-44.

4-34. Stoeckeler, E. G. ; W o o d m a n , R a y m o n d G.; and Farrell,

Robe r t S.: Mul t i d i s c i p l i na r y Analys i s of S ky la b Ph o t ograp h y

fo r Highw ay Eng ineerin g Purposes . NA SA CR-141942, 4-45.

1975.

4-35 . Trumbull , J . V. A. : The Uti l i ty of Sky lab Pho tointe rpre ted 4-46 .

Earth Resources Data in Stud ies of M a r i n e Geology and

Coastal Processes in Puerto Rico and the V i rgin Is lands .

NASA CR-147437 , 1975.

4-36. Colwell, R ober t N .; Bowden, Leo n a rd W . ; e t al.: U se o fS ky l a b Im age ry to Assess and M oni t o r Ch ange s in the

S ou t h ern Ca l i fo rn i a E nv i ro nm e nt . NA S A CR- 1 4 7 5 6 1 , 19 74 .

Bak er , Vic tor R. ; Holz , Robert K. ; e t al .: S t ream Netw ork

An a ly s i s and Geomorphic F lood Pla in M a p p i n g F ro m O r -

bi ta l and S uborb i t a l Re m ot e S e ns i ng Im age ry A p p l i ca t i on to

Flood Hazard Stud ies in Cent ral Texas. NAS A CR- 1 4 4 35 4 ,

1975.

Piech , Ke nne th R . ; Schot t, John R. ; and Stewart , Kento n

M .: S 1 9 0 In t e rp re t a t i on T e ch n i q ue s D e ve lop m e nt an d Ap -

pl ica t ion to New Y ork State Wa ter Resources . NA SA

CR-144499, 1976.

H a n n a h , J o h n W . ; Thomas, Gar land L . ; e t a l. : P lann i ng Ap -

pl ica t ions in East Cent ral F lorida. NA SA CR-145415, 1975.

Yar g e r , Harold L. ; and M cC aule y , Jam e s R .: S ky l a b S t ud y o f

W ater Quali ty . NA SA C R-144505, 1975.

Barnes , J . C. ; Smallwood , M. D. ; and Cogan, J . L . : S tudy to

D e ve lop Im p rove d S p ace c ra ft S now S urve y M e t h od s Us i ng

S k y l a b / E R E P Data. NASA CR-144338 , 1975.

Coop e r , S au l ; And e r s on , D uw ayne ; e t al . : Sk y l ab I m a g e r y :

A p p l i ca t i on to Re s e rvo i r M anage m e nt i n New E n g l a n d .

N A S A CR-144514, 1975.

An ders on, J . R. ; Hardy , E . E . ; and R oach , J . T . : A Land-U se

Classification System for Use W i t h R e m o t e Sensor D at a .

U.S. Geol. Surv. Circ. 671, 1972.

G u m e r m a n , George J . ; Hanson, John A. ; e t al . : The Hy-

drology of Preh is tor ic Farming Systems in a Ce nt ra l Arizona

Ecotone . NASA CR-144492, 1975.

Moore , G. K. : H yd ro log i c Signif icance o f S ky l a b L i n e a m e n t si n C e n t r a l Tennessee. NASA CR-144490, 1976 .

Ban n er ! , Dieter ; Bender , H. ; e t al . : Hydrogeological In-

ves t igat ions in the Pampa of Arge nt ina . NA SA CR-144488 ,

1975.

1 8 8 S K Y L A B E R E P IN V E ST IG A TI O NS S U M M A R Y



Oceans and AtmosphereW l L L A R D J . PlERSON.

afWILLIAME. M A R L A T T ,

b

Z A C K H . B Y R N S ,C

A N D W I L L I A M R . J o H N S O Nd

TE O C E A N O G R A P H I C P R O B L E M S Stud ied in the

Ear th Resources Exper iment Package (EREP) In -vest igations Program included locating the surface of

th e ocean relat ive to the center of the E a r t h as a func-t ion of lat i t ude and longitud e; mea sur ing sea-surfacet e m p e r a t u r e m o r e a c c u r a t e l y w i t h d a t a f r o m aspacecraf t ; descr ib ing th e var ia t ion of ocean color an dthe dynamics o f floating ice in space and t ime; detec t ingocean currents and ocean upwe l l i ng and the spa t ia l andtemporal changes in them; descr ib ing erosion, r iverrunoff , sed iment t r anspor t , and the c i r cu la t ion wi th inbays and estuar ies border ing th e ocean; assessing oceand u m p i n g ; and loca t ing p roduc t ive f ishing areas. Themeteorological problems were those of measur ing c loudfeatures; iden tifying the v er t ical and h or izo ntal dis-tr ibution of aerosols through the atmosphere both

qual i ta t ively and quanti tat ively ; descr ib ing th e radia-tion and energy budgets of the atmosphere; ident i fy ing

character is t ic airmass proper t ies; and measur ing th ewinds in the p laneta ry bou ndary l ayer over th e ocean,as determined by sea-surface roughness, to provide datafo r improve d computer-based nume r ica l wea ther p re-dictions.

Th e w i n d , th e oceans, th e a tmosphere over ly ing th eoceans, and the land are resources fo r m a n k i n d .Because of energy - r esource-use ra tes , N A S A a ndEnergy Research and Development Admin is t r a t ion

aCi ty Univers i ty o f N ew Y ork .

Colorado State U n i v e r s i t y .C

N A S A L y n d o n B . Johnson Space C enter .d Lock heed Elec tron ics Com p any , Inc .

* Principal Invest igator .

programs are designed to invest igate mod ern m ethodsof ob ta in ing energy f rom the winds and the waves .

T h e oc e ans m o d e r a t e a n d i n f l u e n c e c l i m a t e .

Evapora t ion f rom them prov ides the water vapor tha t i st r anspor ted by the a tmosphere to p rov ide ra infa l l fo rth e land. Changes in oceanic proper t ies can cause floodsand drough t . Th e ocean-atmosphere system providescarbon d ioxide fo r p l a n t life, w h i l e acting as a buffer tomoderate var iat io ns in the amo unt of carbon dioxide.The oceans also serve as a mechan ism for the disposalof waste products . Moreover , th e oceans are the m a j o rme ans of transp or t ing the goods of the w or ld in ships . I ti s impor tan t , therefo re , to u n d e r s t a n d se a ice, winds,and waves to improve sh ipp ing opera t ions .

The study of the oceans and the a tmosphere in an in-t e r d i s c i p l i n a r y m a n n e r i n v o l v es m a n y a s p ec t s o f

science and technology. Many features of the oceanh a v e been studied using data obtained by spacecraf t .The G emin i and Ap ol lo miss ions y ie lded ma ny usefulphotographs of coastal areas f rom which oceanographicfea tu res cou ld b e i d e n t i f i e d . Th e meteoro log ica lsatell i tes cu rren tly being used fo r study purposes havedef ined such features of the oceans as the outl ines ofth e Gulf Stream from day to day. Th e operationalmeteorological satellites used by the National Oceanicand Atmospher ic Admin is t r a t ion (NOAA) rou t ine lyprovide such information as sea-surface temperaturesan d Gulf Stream boundar ies .

A ll EREP ins t ruments were used in the s tudy of

oceanographic problems. Th e Multispectral Photo-gr a ph i c Facility (S190) and the Multispectral Scanner

(S192) proved to be most useful in invest igation of estu-aries, bays, and coastlines; th e o ther sensors proved to

189





masses m } and m 2 d iv ided by the square of the distance rbetween them. The equa t ion fo r the grav i t a t i ona l forceb e t w e e n th e E a r t h a nd a s p a c e c r a f t ha d to b egeneral ized f rom th is equa t ion by in te gra t ing over thevolu me of the E ar th w ith a var ia ble den sity assigned toth e vo lume e lements . I t cou ld be expec ted tha t th e

forces ac t ing on a spacec raf t such as Skylab w o u l d differfrom place to place along th e orb i t depend ing on thenat ure of the E ar th below . Such is indeed the case, andth e ac tua l o rb i t of a spacecraf t , especial ly if it be r a t h e rlow, depar ts subs ta n t ia l ly f rom the e l l ipse der ived byN e w t o n . The oblateness causes th e orbit to changeplane re lat ive to the geom etry of the s tars , and the in-homogenei t i es in the distr ibution of mass in the upperlayers of the sol id Ear t h cause the p ath of the spacecraf tto vary about the th eoretical el l ipse by sub stan tial ,measurab le amounts .

Th e prob lem becomes more compl ica ted over th eocean surface because th e surface of the ocean is closer

to these inhomogeneous concen t r a t ions of mass causedby such fac tors as the proper t ies of the large plates thatform th e upper c rus t of the E a r t h . The oceans try toreach an eq uil ibr ium surface determined by an ap-p ropr ia te in tegra t ion over th e masses in the v o l u m e ofthe sol id Ea r th . I f there w ere no win ds genera t ing oceancurrents , if there were no ocean t ides , if there were nocooling at the poles and no h ea t i n g at the E q u a t o r , andif the oceans did not vary in their sal ine content , thenth e surface of the ocean would be level and it wou ld cor-respond to the concep t of the geoid.

Th e ocean is very near ly level because all the effectsci ted cause it to depart from the geoid by at most 2 or 3

m (with a few notable exceptions, such as the t ides inthe Bay of Fundy) , whereas th e geoid moves towardand away f rom th e center of the Ear th by amounts tha tdepar t f rom the el l ipsoid of revolution by as much as1 0 0 m .

S pu t n i k , th e first satel l i te , was launched by theU.S.S.R. in 1957 and tracked by Brit ish sc ientis ts w housed th e measurements of its o r b i t fo r c o m p a r i s o n wi th

previous ly made measurements based on land dis-tances. Th e ell ipticity of the Ear th w as c o n f i r m ed andmeasured independen t ly in th is way . M any subsequen torbi ta l spacecraf t have been tracked very careful ly , andth e per tu rba t ions in their orbits have been used to

ca l cula te some of the charac ter i s t i c s of the geoid.

Before Sky lab , th e problems associated wi th us ingth e orb i t s of other spacecraf t to determine th e geoidwere becoming inc reas ing ly diff icul t to solve becausegreater accuracy was required. This diff icul ty arisesbecause th e effects of the smaller scale var iat ions of thegeoid fade rapidly wi th height and hence have l i t t le

effect on the orbital spacec raf t . A lower l i m i t exists atw h i c h spacecraf t can be orbited before the drag of theu p p e r atmosphere causes them to s low down and fall

back to Ear th ; hence , im por ta n t de ta i l s of the geoid can-not be sensed. Programs were developed to generate ageoid by combin ing spacec raf t measurem ents and thel imi ted n u m b e r of m ea s u r em en t s of grav i ty v ar iab i l i ty

over th e surface of the Earth. The results led tonumerous geo ids , one being the Marsh -Vincen t geo id(or th e Goddard Ear th Model 6 (G E M - 6 ) ) , s h o w n infigure 5- 1 (ref. 5-1).

Th e GEM-6 geoid contours th e depar tu res of the sur-face of the ocean, as con t inued by theory in to the con t i -

nents , in units of meters as if they were measured interms of the distance from th e el l ipsoid of r evo lu t ion .Several features are n o t e w o r t h y . Fo r example , to th islevel of d e f i n i t i o n , th e surface of the ocean is 100 mcloser to the center of the Ear th at a point in the IndianOcean than is the ell ipsoid of revolution. Other areasare as m u c h as 40 or 5 0 m f a r ther f rom th e center of theE a r t h t h a n is the el l ipsoid of revolution. This f iguredoes not r epresen t th e correct geoid because th e com-plete geoid has yet to be measured; never theless , manyof the major features are correct.

Before the Skylab missions, analysis of orbital datamade i t possib le to dis t in gui sh app rox ima tely 20 geoid

oscil lat ions around the E a r t h ; th e shor test osc i l lat ionwaveleng th tha t cou ld be resolved w as a p p r o x i m a t e l y2000 km at the Equator . (The use of precisely obtainedgravi ty measurements a l lowed shor ter waveleng ths tobe determined , bu t gravi ty data are expens ive anddif f icu l t to obtain.) A lt im eter data f rom Sk ylab resolvedoscil lat ions that are 20 km long and thus produced animp rove me nt in spatial resolution by a fac tor of 100 inth e hor izon ta l d imens ion .

An investigation of the problem of combin ing Sky labt rack ing data and ca lcu la t ions of the orb i t wi th thea l t imete r measurements of the distance between Skylaband th e ocean surface w as conducted by M o u r a d et al.

(ref. 5-2). Th e accurate calculat ion of the Sky lab o rb i t

O C E A N S A N D A T M O S P H E R E 1 9 1



>j 12 0 150 180 150Longitude, deg

120

FIGURE 5-1.—The GEM-6 detailed gravimetric geoid w i t h around-the-world groundtrack of a Skylab 4 pass b e g i n n i n g off the coast of Brazil

and ending in the Caribbean Sea (from ref. 5-1). Contour intervals are 10 m; groundtrack segments are numbered from 201 to 226.

over a s h o r t arc depended on precise knowledge of thespacecra f t location and velocity at the star t of the arc. Itw as shown that , fo r reference el l ipsoids that differ inmea n radius by 1 par t in 60 000 and in f la t ten ing by 5par t s in 30000, th e calculated al t i tudes fo r Sky labwould differ by 10 m after tr ave ling on ly 10° oflongitude. The ac tual al t i tud e of Skylab varied by as

m u c h as 1 km over a 1000-km arc. It is necessary todetermine these a l t i tudes to an accuracy of a few metersbefore the f u l l potential of spacecraf t al t imetry can berealized. Large bias t e rms for dif ferent Z-axis- to- local-vert ical passes indicated large dif ferences f rom one or -bi tal segment to another .

Accord ing to Mourad ,

The bias t e rms recovered fo r d i f f eren t segments[were] s ignif icantly dif ferent and had l i t t le or nocorrelat ion with each other . Th e general agree-ment between th e a l t i m e t r y and the a priori geoidprofi les demonstrates the viabil i ty of the al t im etry

techn ique to determine the marine geoid. Th eshor t per iodic deviat ions between t h e m , consider -in g th eir ma gnitud es, [reflected] the high frequ en-cy com pon ents of the geoid. I t is also evid ent th at

the a l t imet ry sensor is very sensitive to the localgeoidal features such as those corresponding totrenches, r idges, and sea mounts . Excel lent agree-ment be tween th e results obtained for the s a meplace at dif ferent t imes (near the Puer to RicoTrench) indicates th e self consistency and preci-sion of the altimeter except in the bias term.

The high-f requency components of the geoid arenever theless easi ly detec ted. Examples f rom th e S193altimeter are given by McGoogan et al. (ref. 5-3). Th efirst pass to be discussed began as the Skyla b spacecraftcrossed th e east coast of the Uni ted States an d pro-ceeded on a southbound orbit across th e island of Puer-to Rico . Th e height of the mean se a level relative to thereference el l ipsoid as obtained f rom the dif ference ofthe al t imeter range measurement and the computedsatel l i te orbit is shown by the i r regular l ine in figure5-2(a). Th e al t imeter trace f luc tuates as much as 1 mvert ical ly over the dis tance tha t was measured. These ir -

regularit ies are caused by the diff icul ty of measur ingtime a ccurately for the noisy re turn of the ra dar pulse inwhi c h a change of 1 nanosecond represents a 15-cmchange in range.




Al t ime te r return f rom

Puer to R ico Is land

2000 -

4 0 0 0 -

6000 -

8000-

-100

(a)

17:15:10

19.8°N68 . 6°W

17:16:00

G M T , hr:min:sec

17:16:50

16.0°N

65 . 3°W

10000

Puer to R ico T rench

17:15:10

19.8°N

6 8 . 6 ° W

17:16:00

G M T , hr:min:sec

17:16:50

16.0°N

6 5 . 3 ° W

F I G U R E 5-2.—Comparison o f S193 a l t imeter data , reference ellipsoid (GEM-6), and s u b mar in e to po g r aphy fo r s o u thb o u n d Sk y lab 2 pass 4

o v e r Puerto R ic o o n June 4, 1973. (a ) Meas u r ed a n d t heo r e t i c a l geoids. (b ) C o r r es po n d in g s u b mar in e to po g r aphy for the P u er to R ic o Tr en c h .

A s m oo t h c u r ve d r a wn t h r ough t he a l t i m e t e r ge o idtrace w o u l d very nea r ly represent the l eve l sur face ofthe ocean . Over the r e la t iv e ly shor t d i s t ance of ap pro x -ima te ly 220 km, the sur face of the ocean is 1 2 m closerto the center of the Ear th above th e 8-km-deep Puer toRico Trench ( f ig . 5 -2 (b) ) because of the va r i a t i on in theforces tha t produce th e "level" sea surface. On theeas tern s ide of the is land is a s l ight dip but no th in g aspron oun ced a s the va r i a t ion over the t renc h . A sec t ionof GEM-6 da ta a long the s ame orb i t i s reproduced infigure 5-2(a). This t race differs from th e altimeter

m e a s u r e m e n t by 20 m east of P ue r t o R i c o and by 30 mnear the lowes t p a r t of the a l t im ete r t race . The 20-md i f f e r en ce could have been caused by an er ror in loca t -ing Skylab in a l t i tude . H ow ever , d i sp l ac ing th e G E M - 6curve so th a t i t co inc ides w i t h t he r igh t -ha nd s ide of thea l t ime te r geoid would s t i l l l eave sub s tant i a l d i f fe rencesfo r t he geoid over the Puer to R ico Trench . The EREPpasses over th e Puer to R ico Trench were repea tedm a ny t i m e s fo r s l ightly d i f f e r en t sect ions of the t r e nc hand s imi la r resu l t s were ob ta ined each t ime .

In f igure 5-3(a) , the a l t imeter geoid t race is shownfrom t he pas s over the Ja seur Seamount in the SouthA t l a n t i c Ocean, eas t of V i t 6 r i a on the coas t of South

A m e r i c a . The wa te r a round the seamount i s 4 km deep(fig. 5 -3 ( b ) ) . The s e a m oun t rises to w i t h i n a p p r o x -i m a t e l y 200 m of the sea sur face . A s s h o w n in f igure

5-3(a ) , the s ea sur face r i s es approx ima te ly 10 m wi threspect to the center of the E a r t h ove r t h i s s e a m oun t .The reference geoid from f igure 5-1 is es sent i a l ly at thesame d i s t ance f rom the cente r of the Ea r th a long th i s

ent i re t rack and , a s the a l t imete r measurements indi -

cate , there is a di f fe rence of 12 m f rom th e left s ide toth e r ig h t s ide of figure 5-3(a ) . A l t imete r da ta f rom a

pass over a seamount near the Cape Verde Islands (fig.5-4) show th e s a m e p h e n o m e n o n . The sea sur facem ove s a w a y f rom the cente r of the Ea r th by a s mu ch as10 m. A smooth curv e throug h the a l t ime te r geoidw o u l d rep rese nt very closely the lev el surface of the seaexcept for minor effects of , a t most , 1 m in these areas .

On e of the s t r ik ing features of the sea bot tom is thec o n t i n e n t a l she l f tha t i s ad j acent to some, but notnecessari ly al l , con t inen tal coas ts . Off the ea s tern coas t

of the United States in the general area of Florida , theedge of the shelf is ca l led the Blake Escarpment . Ass hown i n figure 5-5(b ) , the coas ta l w ater is in i t ia l ly

s ha l l ow , then deepens to 1000 m, and f ina l ly , over avery shor t d i s t ance , deepens to a pp r ox i m a t e l y 4 800 m .

O C E A N S AND A T M O S P H E R E 193



10

I

-

•-

/ G E M - 6

-.WlHVWm^" 'A l t imeter geoid

14:37:20

24.1° S(a) 39.2° W

14:38:20 14:39:20G M T , hr:min :se c

14:40:10

16.1° S31.9° W

0

1000

E 2000£~"a.

< = 3000

4000

5000

j a s e u r Seamount

(bl

14:37:20

24.1° S39.2° W

14:38:20 14:39:20

G M T , hr:min:sec

14:40:10

16.1° S31.9° W

F I G U R E 5 -3 .—C ompar i s on of S193 al t imete r data , reference e l l ipsoid (GE M- 6), and subm arine topograp hy for northbound S kyla b 3 pass 22

o v e r Jaseur Seamount on Sep tember 2, 1973. (a) Measured and theoret ica l geoids. (b ) Corresponding subm arine topograph y .

It is impor tant to note tha t th e altimeter trace (fig.

5-5(a)) varies re la tivel y slow ly over th e weste rn por t ionout to the edge of the depth increase. Over th e Bl akeEscarp men t, the geoid trace moves toward the center ofth e Ear th by 10 m over a very short distance and thenrises sl ight ly over the rise in the sea floor to the east.Th e GEM-6 geoid (fig. 5-1) does not show this verysteep change over the Blake E s c a r p m e n t .

Most of the t ime, the EREP was operated in theE a r t h -v i e wi ng mode fo r only 5 or 10 minutes , a f te rw h i c h the S kylab spac ecraf t was returned to the solar-inert ia l mode . However , on Janua ry 31 ,1974, the ER EP

w as operated in the Z-ax is - to - loca l -ve rt ica l mod e fo rone com plete Earth orbit ; 26 segments of the geoidwere de te rmined fo r this orbit . (Theloca t ions of 23 ofthe 26 altimeter measurements are plotted on the

G EM- 6 model in figure 5-1.)The theoretically derivedgeoid from spacecraf t and gravi ty data locates majorfeatures of the geoid an d, a long this sub spacecraf t track,th e tota l range in the dis tance by w h i c h th e geoid differs

from th e ell ipsoid of revolut ion is a pp r ox im a te ly f r om—40 to 7 0 m. In general , th e S193 a lt imeter measured aposit ion for the geoid tha t r easonably app rox im a ted th etheoret ical curve, as s h o w n in figure 5-6.The greatestdiscrepancies are for segments 202, 203,222, and 223.

FIGURE 5-4.—Comparison of S193 al t imeter data , reference e l l ip-soid (GEM-6), and submarine topography for northbound Skylab 3pass 24 over th e Cape Verde Islands on September 3, 1973. (a )Measured and theoret ica l geoids. (b ) Corresponding sub ma rinetopography. >

1 9 4 S K Y L A B E R E P IN V E S T I G A T IO N S S U M M A R Y



-

- .

-

4 0

;Alt im eter geoid

1 0

o15:40:00

12.6° N(a) 28.6° W

15:41:00

G M T , hr :min :sec15:42:00 15:42:30

19.4° N

22.9° W

1000

2000

3000

4000

5000

6000

7000

Seamount near Cape Verde Islands—-h

8000 J

15:40:00

12.6° N

(b) 28.6° W

15:41:00

G M T , hr:min:sec

15:42:00 15:42:30

19.4° N

22.9" W




,GEM-6

1000

2000

3000.

4000

5000

6000

Blake P la t e a u

».°-o-So.o"r- "•••on

I I

Hat teras Abyssa l P la in

_ J I

(b)

17:11:10

3 1 . 1C

N80. 2° W

17:12:10 17:13:10

G M T , hnmin-.sec

17:14:10

23.1°N72 . 1 °W

F I G U R E 5- 5 . —Compa r i son of S193 al t imeter data , reference e l l ipsoid (GEM-6), an d su b m a r i n e t o po g ra phy fo r so u t hb o u n d Sk y l a b 2 pass 4

f rom th e Bl a k e Es c arpm ent to the Ha t te ra s Abyssal Plain on J u n e 4, 1973. (a ) M ea su red and theoret ica l geoids. (b ) Co rre spo n d i n g su b m a r i n e

t o po g ra phy .

Each of these bursts of rapid f luc tua t ions in thea l t imeter measurement , indica ted as a pass on thisdiagram, could be expanded in to a set of curves s imi l a rto those previo usly show n. Several segments du ringthis around-the-world pass a lso showed some very in-

teresting results.Segments 209 and 212 and the co rrespon ding sub-

mar ine topography are i l lus t ra ted in figures 5- 7 and 5-8,

r espec t ive ly . Segment 209 shows no str iking correla tion

with the sub m a r ine top og r a phy suc h as m igh t be ex-

pected from the sharp increase in the dep th of the oceanrepresented on the left side of figure 5-7(b) . O f interestis tha t the theoretica l geoid (GEM -6) agrees wit h thea l t imete r geoid represented on the right side of figure

5-7(a) and departs signif icant ly from it (by a pp r ox -ima te ly 10 m) on the left side.The deepest point in the ocean is in the Marianas

Trench. The S193 altimeter was operated over this

1 9 6 S K Y L A B E R E P IN V E S T IG A T IO N S S U M M A R Y



-10014:55:00 15:30:00 16:00:00 16:30:00

G M T , hr:miri:sec

F I G U R E 5-6.—Comparison of S193a l t imeter data segments and reference ellipsoid ( GEM-6 ) f o r Sky lab 4 around - t h e - w or ld pass 97 on J a n u a r y

31, 1974.

trench but in a region on l y app rox ima tely 5500 m deep(fig. 5-8(b)) . Never theless , the Marianas Trench pro-

duced a very sharp K-shaped feature in the location ofthe geoid (fig. 5-8 (a)). Such effects on the geoid also oc-cur r ed over the M id -A mer ica n Trench (figs. 5-9(a) and

5-9(b)) .The var iat io n of the geoidal surface towa rd and awayfrom th e center of the E a r t h , as a response to var ia t ionsin submar ine topography , is clear ly indicated in figures5- 2 to 5-5.The sea surface need no t follow every riseand fall on the sea bottom as was s h o w n in these il -

lustrat ions. Some por t ions of the Ear th ' s crust are inisostat ic equil ibr ium; that is , they have r isen or s u n k asa func t ion of mass to ach ieve an e qu i l ib r ium pos i t ion .Other por t ions of the crust near and a t seamounts andoceanic trenches h ave not at tained th is eq uil ibr i um . I fthe seamounts and the t renches jus t i l lustrated were inisostatic equ i l i b r ium, th e geoid would not be expected

to respond to their presence. Over some par t s of theocean , th is isostat ic equil ib r ium very nea r ly exists andno remarkable dif ference in the altimeter geoid is ob-served over such regions (fig. 5-7).

In th e preced ing f igures, the a l t imeter traces repre-sent the level surface of the sea, except for relat ivelyminor ef f ec ts impor tan t to oceanography. These tracesshow tha t , genera l ly , the level surface of the sea movesaway f rom th e center of the E a r t h over seamounts and

toward the center of the Earth over trenches. The esti-ma t es of the geoid that were calculated un t i l about 1968

d id not inc lude these impor tant features and d id notcorrelate very well with plate tec tonics theory . W henth e radar al t imeter concept was first proposed in 1968,

Greenwood et al. (refs. 5-4 and 5-5)pred ic ted tha t th eal t imeter would resolve the detai ls of the geoid so well

tha t th e geoid wou ld begin to show features that wouldb e correctable w i t h plate tec tonics . The i l lus t r a t ionsthat have been presented show that n o n e of the finerscale f luctuations, such as the rapid var iat ion over th eBlake E s c a r p m en t , th e rises over seamounts , and thedips over the submarine trenches, were in any previous

geoidal model . They al l correspond to var ious aspects ofplate tec tonics th eory , and, thus, the theories of geodesyand tec tonics are becoming more integrated.




4 0r

•

2

10

.

G E M - 6

15:29:40

18.1° S< a ) 116.4° E

15:30:30

G M T , hr:min:sec

15:31:30 15:32:30

11.3° S122.0° E

1000

2000

E

5 3000OVr;

4000

5000

6000

f b )

15:29:40

18.1° S116.4° E

15:30:30 15:31:30

G M T , hr:min:sec

15:32:30

11.3° S122.0°E

F I G U R E 5-7.—Comparison of S193 a l t i m e t e r da t a , re fe ren ce e ll ip so i d (G EM -6) , an d su b m a r i n e t o po g ra phy fo r segment 209 of Sk y l a b 4a ro u n d - t he -wo r l d pass 97 o v e r t he In d i a n Ocean, (a ) M ea su red a n d t heo re t i ca l g eo ids . (b ) Co r respo n d i n g su b m a r i n e t o po g ra p hy .

1 9 8 S K Y L A B E R E P I N V E S T I G A T IO N S S U M M A R Y



•

e

t®

|50(VO

:

•G E M - 6 -

15:40:50

14.4° N

( a ) 141.7° E

15:42:00

G M T , hr :mi n :se c15:43:00 15:44:00

22 . 5 N

1 4 8 . 8 ' E

1000

2000

E

e 3 0 0 0ExD

d

4000

5000

6000

. M a r i a na s T r e n ch

15:41:00

14.4° N( b ) 141.7° E

15:42:00 15:43:00

G M T , hr:min:sec

15:44:00

22.5° N

148.8" E

F I G U R E 5-8.—Comparison of S193 al t imeter data , reference e l l ipsoid (GEM-6), an d s u b m a r i n e t o p o g ra p h y fo r seg m en t 212 of Sk y l a b 4a ro u n d - t he -wo r l d pass 9 7 o v e r th e M a ri a n a s Tren ch , (a ) M e a s u r e d and theoret ica l geoids. (b ) Co rre spo n d i n g su b m a r i n e t o po g ra phy .




-

E 3 0

f 20•a

8

NAlt imeter geo id

15:36:50

(a ) 9o!l°W

15:38:00 15:39:00

G M T , hr:min:sec

15:39:50

5.2° N84.0C W

1000

£ 2000

3000

4000 j i I 1

15:36:50

(b) 90.1°W

15:38:00

G M T , hr:tnin:sec

15:39:00 15:39:50

5.2°N84.0°W

FIGURE 5-9.—Comparison of S193 altimeter data, reference ellipsoid (GEM-6), and subm a r i ne t op ogr a p h y for Skylab 3 pass 18over theMid

A m e r i c a n Trench on A u g u s t 11, 1973. (a) Measured and theoretical geoids. (b) Corresponding s u b m a r i n e t op ogr a p h y .

O C E A N I C PROPERTIES

W ater -Surface Temp era t u r e s

S e ns i ng s y s t e m s o n o p e r a t i o n a l m e t e o r o l o g i c a lsatel l i tes rout ine ly acqui re image da ta in the inf ra redregion of the e lec t romagne t i c spec t rum. From these

da ta , t empera tures of c loud tops can be de t e r m i ne d a nd ,if an unob s t ruc ted v iew ex i s ts be tween the s a te l l i t e and

the sea surface, th e t e m pe r a t u r e of the sea surface canbe es t ima ted . Thi s measurement is made us ing onewave length band in the inf ra red . However , it is neces-

sary to apply cor rec t ions , which are p r e dom i na n t l ybased on c l ima to logica l concept s , for the i n t e r ve n i ng at-

m os phe r e .In f ra red m e a s u r e m e n t of sea -sur face t empera ture isdiff icul t because the sur face wa te r i s unde rgoinge va po r a t i on and t he r e is a very sha rp gradient in tem-

pe r a t u r e at the sur face of the sea, such that over a ver t i -

cal d i s ta nc e o f a pp r ox i m a t e l y 5 0 m m , t he t e m p e r a t u r e

decreases by as mu ch as 1 or 2 K, being colder a t the sur-face . Thi s sha rp gradient a l lows for the flow of hea tfrom th e deeper layers of the ocean t h r ough th e air/seai n t e r f a c e i n t o th e a t m o s p h e r e . W h a t i s a c t u a l l ymeasured i s some te mp era ture re l a ted to th i s sk in t em-pera ture , so a smal l correct ion fo r this effect must bem a de .

The bas ic prob lem, however , is t ha t , as the r a d i a t i onf rom the sea surface t ravels toward th e sensor on thesatel l i te , i t i s both a t tenuated by the a tmosphere andcontamina ted by a tmospher i c emis s ion , wi th the resu l tt ha t s ignal s t rength at the satel l i te is usua l ly lower thanit would have been had i t t rave led through a v a c u u m .

The o veral l effect is tha t the infra red tem pera turessensed by the r e c o r d ing i n s t r um e n t can be as m u c h as 8K cooler than th e t e m pe r a t u r e of the sea sur face . Thes ingle wave length band measurements can be correctedfo r this effect ; bu t , because th e correct ion d epend s on

200 S K Y L A B E R E P I N V E S T I G A TI O N S S U M M A R Y





The strength of the passive microwave signalreceived by the SI94 was a function of numerous physi-cal variables as studied by Holl inger an d Lerner (ref .5-7). These var iables inc lude th e a m o u n t of sung l in treflected by the sea surface back to the a n t en n a and thevar ia t ions in tempera tu re , sa l in i t y , and sea-surface

roughness. Th e SI94 data were studied in such a way asto isolate these var iab les to ascer tain whether or not,u p o n r em o v i n g th e effects of all but one cause, th evariabi l i ty due to that cause could be detected.

W hen opera ted over th e ocean, th e S194 obtainedda ta fo r cond i t ions in w h i c h th e oceanic sal ini ty var iedf ro m a p p r o x i m a t e l y 32 to 36.5 parts per thousand . Thesea-surface temperature as prov ided by the FleetNum er ica l W eather Cen t r a l varied f rom app roxim ate ly27 4 to 301 K, and the windspeed ( the cause of sea-sur-face roughness) var ied f rom 0.5 to 24 m/sec .

Holl inger and Lerner developed techniques to calcu-late th e microwave tempera tu re when th e sa l in i ty ,

windspeed , and t empera tu re are k n o w n . T he n , th eeffects of two of these three var iables were removed sotha t th e r em a i n i n g one could be studied. Ref lec ted"sun l igh t" at this wavelength w as el imina ted s i m p l y bynot using those data in which i t was present . The depen-dence on sal ini ty w as qui te weak , and the scatter in themicrowave tempera tu res , after r emoval o f windspeedand tem pera ture effec ts , was 2 to 3 K abou t the theoreti -cal curve. As the sal ini ty var ied f rom 32 to 37 par ts perthousand , th e theoretical tem pera ture curve decreasedfrom 98 to 95 K for a var iat ion of 3 K. The tem peratu rescatter w as larger than th e range of the sal ini t ies .

Near the mo u t h s of r ivers and estuar ies , where th e

sal ini ty can typ ical ly increase f rom values near zero inf reshwa te r to 32 to 34 pa rts per th ous and over 15 or 30km as the ocean is approached , changes in sal ini ty couldbe detected by an instrume nt h avi ng high spatial resolu-t ion. Because oceanographers require sal ini ty measure-me nt s to two signif icant f igures past th e integer values(i n par t s p er thousand), passive microwave systems a renot appropr ia te r emote sensors fo r sal ini ty measure-me nt s in the open ocean.

The sen sitivi ty of the SI 94 to varia tions in sea-sur-f ace temp era tu re w as also s tudied . Th e theoretical curvefo r the an tenna temp era tu re tha t would be measured bythe S194 var ies f rom a pp roxim ately 96 K near a 273-K

ocean t empera tu re , th rough a modes t m a x i m u m 0.5 Khigher at a 288-K ocean temperature, and then dips to94 K at an ocean t em p e r a t u r e of 300 K. Because of theexcessively large point scat ter throughout this range, i t

w as concluded that the SI94, or any other ins t rumentoperat ing at a f reque ncy of 1 .4 GHz, was not suitab le formeasur ing ei ther sal ini t ies or temperatures of the seasu r face on the open ocean.

The last ocean var iab le studie d (ref. 5-7) in S194m ea s u r em en t s was the dependence of the passive

m i c r owa ve t em pera tu re on windspeed . The passivemic rowave tempera tu re increased f rom app roxim ate ly96 K to a p p r o x i m a t e l y 103 K as the windspeeds var iedfrom 2.6 to 25 m/sec for the passes that were studied. Aregression l ine yielded an equation ind icatin g tha t thepassive microwave temperature increased at a rate of0.31 K per 1-m/sec increase in windspeed . Th e regres-sion equation that was obtained for antenna tem-pera tu re is given by Ta = 0.31 W + 95.2, where W isth e windspeed in meters per second. Th e mean-squaredifference between the windspeed predic ted f rom thepass ive mic rowave tempera tu re and the "obse rved"windspeed, af ter removing al l these other effec ts by

mea n s of theoretical considerat ions, was app rox ima tely4 m/sec . The te mp erature v ar ied app rox im ate ly 10 or 15percent about an average va lue of 98 K.

A ll the resul ts obtained in this invest igation were an-t ic ipated, except for the relatively high scatter of thedata. The theories concern ing ins t rumen t measurementcapabi l i t ies were ver i f ied remarka b ly well . The exper i-m e n t w as successful in ver ifying th e theory of them i c r owa ve emission of the sea surface at a f requency of1.4 GHz. W ith the theo ry conf irmed at this par t i cu l a r

f requency , measurements at a d i f f eren t f r equency , atwh i c h a greater sensit ivi ty to var iat ions in sea-surfacetempera tu re exists, m ay ult imately permit th e deter -

m i na t i on of sea-surface temperature through c louds. Infact, two f ive-frequency scann ing pass ive mic rowavesystems are being bui l t for use on the Seasat-A andNimbus satel l i tes ; theoretical ly , these ins t ruments will

be capable of dete rmin ing sea-surface tem perature, sur -face windspeed, and other sea-surface parametersthrough clouds.

W a te r Depth

The conventional methods of ascer taining waterdep th off a given coastl ine are sounding (drop ping al ine from a ship and determin ing when it h i t s th e bot-

tom) and echo ranging (sending a sound pulse to thebo t tom and measur ing round - t r ip t r avel t ime) . Bo thmethods r equ i r e cons iderab le t ime and ex t r emely ac -curate navigation so that th e pos i t ion of the ship as a

202 S K Y L A B E R E P I N V E S T IG A T IO N S S U M M A R Y



func t ion of lat i tude and l ong itud e is kno w n for eachmeasurement . The mo s t impor tant areas for the deter -mination of depth are those in which the water depth isl ess than approximate ly 30 m. Large amou nts of m o n eyare spen t an nua l ly by the m ar i t im e na t ions to upd a tetheir water -depth char ts , especial ly in areas of impor-

tan t harbor s and ac t ive nav iga t ion . Over th e course of10 , 20, or 30 years, th e dep ths of the water in a givenregion can change. Sandbars can shif t their location,new shoals can fo rm, and other s can be eroded away .The prob lem of correct ly descr ib ing th e dep th of thewater is thus an ongoing problem that requires con-t inuous correc t ion of navigational char ts .

In ocean areas characterized by clear w ater , sunl ig htin th e blue-green por t ion of the s p ec t r u m can penet r a teto cons iderab le dep th . Al though somewhat a t tenua ted ,th e l ight can be reflected from th e bottom and t ravelth rough th e water to the spacecraf t , if no clouds arepresent and if the bottom is not excessively deep. This

technique is unusable where the water is turbid or dis-colored, but, over large areas of the ocean, bottom-ref lec ted l ight can be viewed by the spacecraf t and im-aged by either a camera or a scanner system such as theSI92. Trum bull (ref . 5-8) repor ted th at a stereoscopicview of the bottom could be seen using S190 photo-g raphs . He stated t h a t it is possible to separatebathymetr ic detai l and turbid water effec ts by means ofmul t i spec t ra l in fo rm at ion in the pho tographs and in themul t i spec t ra l scanner data. Images f rom the waveleng thrange 0.6 to 0 .7 /xm show only tu rbid ity features , butimages f rom the wav eleng th range 0.5 to 0 .6 / j ,m show

both ba thymetr ic and tu rb id i ty f ea tu res .

Accord ing to Polcyn and Lyzenga (ref. 5-9),

The radiance observed over shallow water is theresul t of sunlight ref lec t ing f rom th e bottom andth e water surface, as wel l as of the scatter ing ofsun l igh t by the water and the a tmosphere . Tha tpa r t of the signal resul t ing f rom bottom ref lec t ioncon ta ins in fo rmat ion abou t th e dep th of the w a t e rth rough which th e l igh t has passed. In order toext r ac t th i s in fo rmat ion , one must f irst separateth e bottom-ref lec t ion s ignal f rom th e rest of theobserved signal, and then de termine how this sig-

nal is related to the water dep th .

The two unwanted effec ts in the spacecraf t imagesare the scatter ing of l ight by the in terven ing a tmosphere

and the specular reflection of dif fuse skyl ig ht by th ewater surface. These effects produce a background sig-nal that must be sub t r ac ted to obtain useful data. Tod e t e r m i n e th e a m o u n t of unwanted s igna l to besub t r ac ted f rom the signals where th e bottom has been

imaged , da ta mus t be col lec ted over deep water where

there is no bot tomref lec ted s igna l . W hen th e u n w a n t e dsignal is sub t r ac ted , a measured br ightness remains thatcan be related to dep th and other ph ys ica l parameter s .These parameter s are the a tmospher ic t r ansmi t tance ,th e so la r i r r ad iance on the water surface, th e bot tomref lec tance, the inde x of ref rac t ion of water , the l igh t at-tenuatio n coe ff ic ient of the wate r , the angle of observa-t ion (af ter ref rac t ion under water) , and the solar zenithangle (af ter ref rac t ion under water) . Some of theseparameter s can be calculated f rom theory; others haveto be determined for the area in w h i c h th e dep th is to becomputed . In p a r t i c u l a r ,the attenuation coeff ic ient andth e bottom reflectance need to be determined fo r each

area. Var ia t ions in bottom cover can cause differencesin ref lec t ion.

Three methods fo r ext r ac t ing d ep t h i n f o r m a t i o nusing th e theory just described were developed . Onewas a single-band method. Another used tw o bands andexploited dif ferences in bottom ref lec tance and under -water l ight a t tenua t ion d i f f erences . The th i rd com binedtwo bands of i n f o r m a t i o n in an opt imum-dec is ion tech -n ique .

The theor ies were appl ied to S192 data obtained overeas tern Lake Mich igan and the western coastal watersof Puer to Rico . The resul ts of the analysis of the lat terarea are shown in figure 5-11. Th e vertical axis in the

figure is loga r i thm ic and shows the scale for the br ight-ness of the p o i n t in the image minus th e deepwaterbrigh tness level (V - V s ) . Ca l ibrat ion points (squaresfo r band 3 and circles fo r band 2) are points fo r w h i c hth e depth is k n o w n . The agreement is quite good to adep th o f app roximate ly 16 m.

These theories were used to produce a b a t h y m e t r i cch art (fig. 5-12(a)) for the wa ters off the we stern coastof Puer to Rico with the use of S192 data f rom bands 2and 3. For the same region, th e conven t iona l dep thcha r t with soundings in fathom s is shown in figure

5-12(b). Over th e Escollo Negro region, tw o line seg-me nt s were selected fo r ver if i cat io n. Line 1450 of the

digi t ized version (f ig . 5-1 2(a)) was located and com-pared with the conven t iona l ba thymetr ic char t , asshown in figure 5-13. In such a verification effort, theobserved depths are j us t as ques t ionab le as the Sky lab

O C E A N S A N D A T M O S P H E R E 203



s o

50

a

Band 3: Vs = 65

Band 2 : Vs • 130

10W a t e r depth, m

15

F I G U R E 5-11.—Plot of S192 b a n d 2 (circles) and b an d 3 (squares) signals as a func t i on of depth fo r Skylab 2 pass 6 o v e r Escollo N e g r o , Puerto

Rico, on June 9, 1973.

de p t h s because of the l imi ted accuracy and the spot t i -ness of da ta ob ta ined by convent iona l m e thods . Th eagreement is qui te good.

A p p l i c a t i o n s to upd a t ing wor ld naviga t iona l cha r t sa nd m a pp i ng c ha nges i n ne ar - sho r e b o t t om t opog r a ph yare forecast, based on the resul ts that were obtainedfrom ana lys i s of the S kylab da ta .

Floa t ing Ic e

According to Campbel l e t a l . ( ref . 5-10) , pack icebegins to form in the Gulf of Saint Lawrence in Decem-ber and reaches it s m a x i m u m e x t e n t in March , a f t e rw h i c h i t begins to mel t and retreat . At that t ime of theyear , the ice interferes with shipping; therefore , i t i s im-po r t a n t to unde r s t a nd th e growth and m o v e m e n t of thisice as an aid to safe navigat ion. The gulf ex tends f roml a t i t ude 45° to 50° N and f rom ap pro x im a te ly longi tude

58 ° to 68° W.Th e Sky lab orb i t enab led th e S k y l a b 4 as tronauts to

obta in photographic and s canner da ta for the program

conducted by Campbel l e t a l . Because of the 50° incl ina-t ion of the orbi t , success ive ascending nodes groupednear la t i tudes 50° N and 50° S . Consequent ly, Skylabpassed over the gulf on J a nua r y 6 , 11 , 14 , 18 , 19 , 2 0 , a nd21, 1974, dur ing day l ight hours , and hand he ld- cam erap h o t o g r a p h s were obtained on a l l 7 days except forJ a n u a r y 14, wh en S190A and S190B photo graph s andS I 92 imagery were ob ta ined .

T h e sk ies w ere unu sua l ly c l ea r, and the pho t og r a phsenabled id ent if ic at ion of man y ice , c loud, and snowfeatures in the gulf region. In wi n t e r , m a ny of the ex-t r a t ro p ica l cyclones that form over the United Statesdeepen as they move nor thward and ob ta in full

deve lopment a s they t rave l toward the gul f ; t hus , t h i sarea is one of the clou dies t and w indies t regions ofN or t h A m e r i c a . In the polar regions of the wor l d , th ec on t i nuous and ef fec t ive mapping of f loa t ing ice bye i t he r pho t og r a ph i c o r inf ra red imaging sys tems one i the r a ircraf t or spacecraft is prevented by clouds .

In suppor t ing the S kylab da ta acqu i s i t ion , twoaircraf t , an oceano graphic sh ip , a h e l i copte r , th ree a i r -cushion vehic l es , and t rucks were used to acqui re




H i i •

-480

- 4 6 0

! - 420

- 4 0 0

3 8 0

: - 3 4 0

i[:jj--320:!!;!:

Line 1440 1450

Scale, km\

FIGURE 5-12.—Area of f western coas t o f Puer to Ri co . P u n t a G u a n a j i b o is at the up p e r r i gh t - h and corne r . The num be rs to the r i gh t of f igures

5-12(a) an d S-12(b) ar e digi tal point numbers p lot ted in f igur e 5-13. A ltho ug h f igures 5-12(a) an d 5-12(b) do not co i nc i d e ge om e t r i c a l ly , th egeographic area cove re d by bo t h f i gure s is ap p rox i m at e ly th e s a m e , (a ) Color- cod ed ba t h y m e t r i c ch ar t ob t a i ne d f rom ana lys i s o f S192 band 2 and

3 da ta . Th e shallowest dep ths a re red ; th e deepes t , b l u e , (b ) U.S. Coast a nd Geodet ic Survey chart o f cor re s p ond i ng a re a ( f rom U .S . D e p ar t m e nt

of Comm erce c hart 25671) wi th dep ths in f a t h om s . Th e l ine an d point numbers were ext rapolated from f i gure 5-12(a).

r emote ly sensed data du r i ng th e Skylab overpasses. As ide-looking imaging radar at a 3-cm wave length w asused on one aircraf t , and a pa s s ive m ic r ow a ve imagings y s t em w a s used on a no the r . O the r aircraft i n s t r um e n t si n c l u d ed a n i n f r a r e d s c a n n e r , a m u l t i f r e q u e n c ym i c r o w a v e radiomete r , and two RC -8 cameras . The

ships and the hovercra f t were used to ob ta in pho to -graphs and to measure ic e g r ow th , ic e th i c k ne s s , an dother condi t ions . The truck s ob ta ined da ta on ice nea rthe shores.

Examples o f the spacecra f t imagery ob ta ined overth e gulf from J a nua r y 14 to 21, 1974, are show n in




-

1 5

:

Calculatedi Sk y l ab )

5 2 0 « W O 400

P oint number4 2 0 -< 461 4 8 0

F I G U R E 5-13.—Comparison of ca l cu l a t ed and cha r t ed depths a long l ine seg m en t 1450 (figs. 5-12(a) an d 5-12(b)) in the Escol lo Negro , P u er t oR i c o .

figures 5-14 to 5-17. Figu re 5-14 shows details of the icesuch as color, leads, and coverage around Pr ince Ed-ward Is land on J an ua ry 14. The ice cover was not as ex-tensive as it was on J a n u a r y 18. The p h o t o g r a p h s onJ a n u a r y 20 document a r emarkab le g rowth of the iceover a 2-day period; th e rapid eastward extension of thearea covered by ice is also evident. Th e exten t of openwater areas around Anticost i I s land had changed ap -preciably .

Figure 5-18 is an ice reconnaissance map of the gulffo r Ja nua ry 18. This m ap (one of four in ref. 5-10) is anoperational real - t ime product that uses NOAA-2, Land-sat, and aircra f t reconnaissance data. Althou gh th eSkylab pho tographs were no t used in preparat ion of the

m a p , t here is general agreement between th e pho to -

graphs and the map. Differences can be seen, however(e.g. , the area of open wate r south of A nticost i I s land ).Th e s t r eaming and the ed d y i n g of the ice to the sou th -east of A nticost i I s land are imp or tan t and t he ir changeswere traced from an alysis of the other photog raphs.

Th e aircraft program yield ed data f rom active and

passive microw ave systems th at were analyzed to infer

th e age of the ice. An e xam ple of a s ide- looking ima gingrada r prod uct is show n in f igure 5-19. The am ount of in-formation in side- looking airborne radar imagery is im-

pressive: pressure ridges, shear ridges, f loes of all sizes,and plumes are c lear ly discernible. The radar data cur -rent ly are useful for inte rpre tat io n of the surfacefeatures of ice but cannot provide info rma tion on the

age and thickness of the ice.




•• .

•k r L :3k. - v rf* x

NP.-r'^"^ ' . . . . v* «

F I G U R E 5 -14 .—Skylab 4 color photographs of Prince E d w ard I s l and and t h e G u l f of Saint La wren ce taken on Jan ua ry 14 , 1974. (a) S190A

(SL4-69-058). (b ) S190B (SL4-93-041).




.

T V C a pe W o l f e

^ \ ,n£ - a s

& ::;vj

,./J::i ;'•-'-

> ;

. 1 -;;

"' • «^ asLfil BS- " '

,„. Egnxint"

- , _ B a y

&^*-~- .*\. • -. * »

',/

- y

v ^rr^V

:? IK

> •N> ,' *- <•" Cape'ToM ttentirte iT**" ^*.

k\ ; •l§ :f

nGURE 5-14.—Concluded.




B e l l e I s l e

Strait of B e l l e Isle

N e w f o u n d l a n d

L a b r a d o r

G u l f o fS a i n t L a w r e n c e

a c q u e sCartier

P a s s a g e , ^

"Anticosti Island

F I G U R E 5-15.—Skylab 4 c o lo r p h o t o g r a p h ( h a n d h e l d c a m e r a ) of the Gulf of Sain t Lawrenc e th rou gh th e Strai t of Belle Isle, viewed o b l i q u e l yto the nor th eas t , taken Ja nu ary 20, 1974 (SL4-141-4331).

O C E A N S A N D A T M O S P H E R E 20 9



F IGUR E 5 - 1 6 . —S ky lab 4 co lo r p h o t ograp h s ( h a nd h e ld c am e ra) o f w e s t ern Gul f o f S a i n t L aw re nce and t h e Gaspe Peninsula. Because of photo-

g r a p h o b l i q u i t y , s c a l es ar e a p p r o x i m a t e , (a ) J a n u a r y 18 , 1974 (SL4-140-4215). (b ) J a n u a r y 20 . 1974 (SL4-141-4321).




F I G U R E 5 -16 .—C onc luded .




FIGUR E 5-17.—Skylab 4 color photographs (handh eld camera) of northwestern Gulf of Saint Law rence and Ant icost i Island, (a) Janu ary 18,1974 (SL4-I40-4216). Scale is a p p r o x i m a t e , (b ) J a n u a r y 20, 1974 (SL 4-141-4327). (c ) J a n u a r y 21 , 1974 (SL4-141-4366).




F I G U R E 5 -17 .—C ont inued .






50 -

45 l-60

Longitude, d e g W

FIG U RE 5-18.—Ice reconnaissance map of the Gulf of Saint La wren ce fo r J a n u a r y 18 , 1974, prep ared from aircraft an d sa te l l i te da ta . Tota lconcentra t ion is expressed in t en ths (i.e., 1-3/10 = 0.1 to 0.3; 7-9+/10 = 0.7 to >0.9); t en - ten ths (10/10) is equivalent to 100 percent .

Data from the a irborne passive microwave imagingscanner are shown in both horizonta l and verticalpolar izat ion in f igure 5-20(a). Sup portin g aircraft photo-

graphs of different types of ice are shown in figures5-20(b) to 5-20(d). The microwave temperature (fig.

5-20(a)) is color coded from red as the " w a r m es t " d o w nthrough th e color spectrum as an aid in visual in -t e r p r e t a t ion . Th e b r igh tne s s t e m pe r a tu r e (a termequivalent to the passive microwave temperature) isdifferent for the two polar izations and for different








Fisheries, Chlorop hyl l , W a te r Color , a nd Produc t iv i ty

Th e world f i sh ing e f for t explo i t s an ocean resource.

The to ta l we ight of all the fish caught by the m a j o r fish-

ing nat ions increased to a peak in 1972 and t hendecreased in both th e f o l lo win g years . This t rend sug-gests that certa in areas are be ing overf ished and t h a t th em a n a g e m e n t of this resource has no t been directedt owa r d th e c onc e p t of m a x i m um s us ta i na b le y ie l d .

The presence of fish in a certa in area of the ocean de-pends on the a va i l a b i l i ty of food in the forms ofz o o p l a n k t o n a n d p h y t o p l a n k t o n . P h y t o p l a n k t o n , b e in gsmal l p l ant s , requi re the equiva lent of fer t i l izer and

s un l i gh t . Th e fer t i l izer , ca l l ed nut r i en t s , consists of thedi s so lved n i t ra tes , ph osph a tes , a n d c a r b on c om poundsin t he w a te r . Because sun l ight only pene t ra tes the f i r st

100 m of the ocean , th e food cha in in the oceans andes tuaries s tarts in the surface layers .

In many a reas of the ocean, th e nu t r i e n t s are no t

a b und a n t e nough to s u p p o r t th e food ch a in an d p r oduc elarge num ber s of f i s h . M idocean a reas a t l a t itudes 30° Nand 30° S , wh ere the sur face wa te rs s in k , a re p ar t icu la r ly

devoid of nut r i en t s .Th e ocean areas in whi c h nu t r i e n t s are p len t i f u l are

coastal areas with r ive r runoff , Arc t i c and A nt a r c t i careas w h e r e th e water over turns each winte r to b r i ngs ub m a r i ne nu t r i e n t s to the surface, a n d u p w e l l i n g areasof f the western coas ts of cont inents a t certa in la t i tudes .In these up we l l ing areas, th e genera l c i rcu la t ion windsb l ow t owa r d th e E q ua t o r , and the drag of the w i n d o nthe sea surface forces th e coasta l water out to sea andt h u s causes nut r i en t - r i ch co lde r wa te r f rom several

hundred mete rs be low th e surface to rise.Numerous inves t iga t ions have indica ted tha t wa te r

w i t h cer ta in co lors , p rob ab ly caused b y ph yto pla nk ton ,a n d c e r t a i n t e m p e r a t u r e s , o f te n r a t h e r n a r r o w l ydef ined , are prefe r red by va r i ous species o f f i s h . If theseregions of the ocean could be located, fishing vesselsconce ivab ly could b e directed to t h e m . Th e resu l t wouldbe a reduc t ion in the cost of f ish and an increase in theav a i lab i l i ty of these fish to the c ons um e r .

N um e r ous p r ope r t i e s of the ocean surface can beremote ly sensed as an aid in l oca t ing p otent i a l fishingareas . These propert ies , ca l led s ignatures , need notnecessari ly be the same fo r every area. Those t h a t can

ind ica te th e presence o f a b u n d a n t p h y t o p l a n k t o n areth e t empera ture va r i a t ions and the diverse colors of thewa t e r . Th e dis t inct ive colors of the water m a y b e caused

by th e presence of c h l o r o p h y l l or by suspended sedi-men ts tha t may ind ica te nut r i en t - r i c h runoff .

Severa l inves t iga t ions wi th in the overa l l concept of

fisheries were concerned with detect ion of the nut r i en t -r ich po r t i ons of the sur face wa te rs in oceans, bays, andes tuaries by m e a ns of some direct s ignature that could

be sensed by the S kylab ins t ruments . E ight repor t s a reof interes t : Pir ie and Stel ler ( ref . 5-11) , Nichols (ref .5-12) , Gordon and Nichols (ref . 5-13) , Marshal l andB owk e r (ref . 5-14) , Kor b and Pot ter ( ref . 5-15 ) ,Szekielda (ref . 5-16) , W atana be et a l . ( ref . 5-17) , and

Savastano (ref . 5-18) .Areas of upw el l ing occur a long the con t inenta l coas t

and are the locat ion of important f isheries . Coasta l up-wel l ing occurs when winds b low ing pa ra l l e l to theshore l ine or s l ightly offshore cause th e wa r m s u r f a c e

wa te rs to move seaward . To replace that loss , watersfrom depth r i s e to the surface. Th e subsurface wa te rsare cooler and contain more nutr ients . Pir ie and Stel ler

( ref . 5-11) and Szekielda (ref . 5-16) used EREP data tos tudy t h i s phe nom e non off the Ca l i forn ia and We s tAfr ica coasta l areas , respect ively.

A n i l l us t ra t ion of the sensing of upw e l l i ng u s ingEREP data is shown in f igure 5-21. The l ight areas inth e wa t e r are caused by suspended sediments borne byth e r ivers that discharge into th e ocean a long this por-t ion of the Ca l i forn ia coas t. Th e suspended sedimentsf low s ou t hwa r d a l ong th e coast and spread ou tward in toth e ocean a t discrete regions . (The arro ws ind icate cur-rent d i rec t ion . ) Thi s mix ing of the coastal water con-t a in ing th e suspended sediment wi th th e offshore wa te ris not very e f f i c i ent , wi th th e resul t t ha t sha rp bound-

aries between the offshore water and the coas ta l turbidwa te r can be seen. The five fingerlike proj ec t ions in theu p p e r lef t po r t i on o f t he f i gu r e i l l u s t r a t e t h i s

p h e n o m e n o n . Three regions (U ) t ha t are not i ceab lyda rker than th e sur roundings represent a reas wi thoutth e tu rb id i ty associa ted w ith the r iver water . Based onth e locat ion of these regions , oceanograph ers w ouldconc lude tha t they are composed of water tha t has up-wel led f rom th e deeper layers to the west.

Similar effects can be detected in the imagery ob-t a ined by opera t iona l spacecra f t , a s shown in f igure5-22. This imag e, obtain ed September 11, 1974, fromN O A A -3 da t a ( r e f . 5 -19 ) , i l l u s t r a t e s th e s a m e

p h e n o m e n o n on a wi de r scale off the Cal i forn ia andOregon coasts. In t h i s the rma l - inf ra red image , l ightshades in dic ate cold water; dark shades , warmer wa te r .




S c a l e , k m

F I G U R E 5-21.—Skylab 4 S190A photograph of the nor thern Cali -fornia near-shore a rea taken on January 26 , 1974 (from ref. 5-11)

(SL4-78-069).

0 100S c a l e , k m

F I G U R E 5 -2 2 .—Therm al - in f r a r ed image of s ea - s ur fac e t em-

peratures off the C a l i f o rn ia an d Oregon coast ( N O A A - 3 i m a g e ac-

qu i red September 11 , 1974).

The l ight gray along th e coast is w a t e r w i t h a tem-

pe ra tu re of a p p r o x i m a t e l y 287 K, and the dark g rayof f shore represents t empe ra tu re s approximate l y 6 Kw a r m e r . Th e locat ion and the st rength of the u p w e l l i n g

areas a l ong th e coas t a re readi ly visib le in t h i s image ;

th e general pat terns a re s imi l a r to those seen in figure

5-21. Th e upwe l l ed wate r mixes wi th th e r i ve r wate r .

T h e resul t m a y b e h igh nu t r i en t concen t ra t i on in theupwe l l ed wate r , mode ra t e concen t ra t i on in t he mixed

river and upwe l l ed wate r , and low nu t r i en t concen t ra -

t ion in the offshore water .E x a m i n a t i o n of bo th these images shows that sharp

boundary l i ne s r ep re sen t ing zones of d i s c o n t i n u i t y be-

tween tw o k i n d s of surface water ar e seen as far as 50k m f r o m shore. M o s t c o n v e n t i o n a l s h i p b o a r doceanographic measurement techniques cannot de l ine-

a te these ve ry compl i ca t ed pa t t e rns . Thus, r em o t e sens-

in g provides oceanographers wi th th e abil i ty to resolve

new scales and to invest igate new p r o b l e m s in the cir-cu l a t i on of the coastal waters . A review of theoceanograph i c l i t e ra tu re more t han 10 years old woul d

reveal that most phys i ca l oceanographe r s we re unawa re

of th is scale of c o m p l e x i t y in sea-surface proper t ies .

That upwe l l i ng—or th e absence of i t—along th ewestern coast of N o r t h A m e r i c a is i m p o r t a n t i n f o r m a -tion desired by the f i she ry indus t ry is s h o w n in the re-




cent w ork of B aku n (ref . 5-20) and B ak un and Nelson(ref. 5-21). The first reference provides a t abu la t ion ofthe d a i ly and week ly up we l l ing in tens i t ies a long thewestern coast of North America f rom 1967 to 1973. Th esecond d iscusses the me t hod b y which these quan t i t i esare computed and describes th e c l i m a t o l o g y of u p w e l l -in g processes off the coast of Baja C a l i f o r n i a .

These tw o studies , al though not a p a r t of the E R E PProgram, show h ow upw el l ing pa t te rns de termined

from imagery cou ld ev en tua l ly be cor r e la ted wi th w i n d smeasured by a radar scat terometer . In both cases , thedetails of the w ind f ie lds near th e coast are determinedfrom the conven t iona l meteoro log ica l in fo rmat ion andare then used to c o m p u t e th e stress of the w i n d on thesea surface, th e cur ren ts p roduced by th i s stress, and thearea of u p w e l l i n g . Th e volume of water tha t may be in-volved in the upwe l l i ng seen in f igure 5-21 wa s calcula t-ed to be as m u c h as 343 mVsec per 100 m of coastline.T h e a m o u n t o f upwe l l i ng peaks in June and July and isstil l near ly always present both at l a t i tude 3 9° N ,long i tude 125° W, and a t l a t i tude 36° N, longitude 122°W , in September . Fo r both areas, weekly averagesusual ly exceed 50 mVsec per 100 m of coast l ine withp ea k a m o u n t s as high as 250 mVsec per 100 m ofcoastline.

An oceanic region similar in c ircu lat ion and c l ima teto the region off the western coast of N o r t h A m er i c a isof f th e coast of Spanish Sahara an d M a u r i t a n i a in anarea f rom lat i tud e 18° N to 22° N, longitude 16° W to18° W . The w el l - k n o w n u p w e l l i n g p h en o m en on in th i sarea is caused by meteorological condit ions s imilar tothose off Cal i forn ia (ref . 5-16). A n S190A color p hoto-graph off Cape Blanc , wh ere the land is deser t, is shownin figure 5-23. The different colors of the water areclearly ev iden t .

Numerous images f rom both Landsat-1 and Sky labh a v e been obtained fo r th is region and were used tomap the ocean color bou nda ries (fig. 5-24). The plotsrevealed that th e boundar ies f luc tuate d f rom 10 to 20 toperhaps 40 km from one image to the next and tha t theywere quasi-persis tent features of the sea surface in tha tarea. (A feature is def ined as quasi-persis tent if it lastsseveral weeks before marked change is observed.)

Analys i s of the EREP da ta shows tha t upwel l ing

features are relat ive ly small scale com pared to majoro c ea n f ea t u r e s s t u d i ed b y m e a n s o f s h i p b o a r doceanograph ic m easurements . The same features wereobserved in the im agery off southe rn Ca liforn ia, and i tis ev iden t tha t r emote- sens ing techn ique s make it possi-

ble todel inea te

theseareas more accu rately . Because

th efeatures are quasi-persis tent , ample t ime exists for af ishing fleet to reach th e more p roduc t ive areas.

M a n y fish caugh t in the con t ine n ta l she l f water s offthe U.S. east coast are adults that matured f rom fry inth e nearby estuar ine areas . The f ish are hatched in theestuar ies and spend the ir ear ly years in the marshes andshal low areas u n t i l they are large enough to venture tosea . Under s tand ing th e processes and the p h e n o m e n o nof these estuar ies is thus impor tant in f ishery research.A productive food chain in and near th e m o u t h s oft h e s e e s t u a r i e s r e q u i r e s d i s s o l v e d n u t r i e n t s a n dsun l igh t , th e same essential condit ions that are presentoff Cal i fornia and nor th Africa. The dissolved nutr ientsare der ived through runof f f rom the adjacent landmassand by means of the treated and untreated sewageeffluents that are discharged by the coastal cities andtowns. A sub stantial amo unt of the fer t i l ize r tha t isused by farmers on their f ields is dissolved by rainw aterand carr ied by smal l s t r eams and brooks into these estu-aries as a continuing process .

In con t r as t to upw el led water, the nu t r ien t - r iches tuar ine water can have man y d i f f eren t o r ig ins .Pe r h a p s a pr im ary ind ica to r of its or igin is the wa ter col-or, which depends on the a m o u n t of sed iments tha th a v e been washed down wi th the water f rom the l and .Three investigators (refs. 5-12 to 5-14) attempted toclassify as to c h l o r o p h y l l and produc t iv i ty ind ices th esurface features of the water s off the U.S. east coastnear A ssateague Is land , in the lower Chesap eake B ay,and in the R a p p a h a n n o c k R i v e r . The resul ts were onlypar t ly successful in these par t i cu la r cases an d showedno discernible water -color parameter in the imagerytha t cou ld be s t rong ly cor re la ted wi th ch lo rop hy l l in thewater and on ly a fair correlation of c h l o r ophy l l wi th tu r-bid i ty .

The overal l resul t of the s tudy was that i t was possi-b le to c lassify the estuar ine w aters into num erous majo rcategories according to color an d tha t these categories




F I G U R E 5-23.—S190A co lor p h o t ograp h of C ape B lanc a r ea an d offshore water s ac q u i r ed September 4, 1973 (SL3-84-360). A n area of u p w e l l -

in g is o u t l i n e d .






informat ion obtained by Skylab and by h igh - a l t i t udeaircraft that overf lew th e area simultaneously. Th e p r i -m a r y purpose of the experiment was to ascer ta inw h e t h e r remotely sensed data could be correla ted withsurface measurements and w i th the types and num bersof fish tha t were caught .

Conventional meteorological and oceanographic dataobtained d urin g this investigation were ocean dep th,w a v e condi t ions , d is tance f rom th e shore , ch lorophyl lcontent of the water , sea-surface temp erature , sa l in ity,water t r anspa rency , wa te r co lor , a tmospher ic sur facepressure , and a ir tem pera ture . The water temp eratureswere sensed remote ly by two different aircraft over ap o r t i o n of the tota l area t h a t w a s i nve s t iga t e d .C hl o r ophy l l - a w as sensed remo tely and measured a t thesurface. The remotely sensed chlo roph yl l da ta w ere ob-ta ined by a specia l spectra l radiometer f lown on a l ight

aircraft at an a l t i tude of 3000 m. The ins t rumentmeasured the radiance in the spectra l region from 390to 1100 nm and was calibra ted at 57 wave lengths in thatr a n g e . A n i m p o r t a n t f e a t u r e i n t h e m e a s u r e dc h l o r ophy l l content of the waters near the surface of the

Gulf of Mexico is t ha t it varies by fairly large amountsover re la tively small areas. Th e content can be as m uc has four times greater in one place than it is in a no the rjust a few kilometers aw ay, and sm all pockets or regionsof zero chloro ph yll-a have been observed. The correla-t ion of the values of chloroph yll-a , as measured from an

ai rcraf t and as measured from water samples obta inedin situ for one fl ight l ine , is shown in figure 5-25.The fish involved were th e blue marlin, th e white

mar l in , the sa i l f ish (und er th e classif ica tion of bi l l f i sh) ,and the dolphin and wahoo (under the classif ica tion ofothe r game f ish) . Dur ing a 2-day period, 67 f ish were"raised but not hooked," w hic h p r ob a b ly mea n s tha tthey were sighted and followed th e ba i t for a w h i l e butdid not take the bai t . Of the 171 f ish that were hooked( a pp r ox i m a t e l y th e same num ber on each d ay) , 58 gota wa y ; therefore , 113 fish were caught.

Models based on aircraft data and conventional sur-face-truth data were developed fo r predicting th e abun-dance of w hit e marlin in the area . The best model usingthese techniques had a correlation coefficient of 0.489and was significa nt at the 60-percent level. The effect of

I

I 3£IIr

R emote measurement

O Surface measurement

I

0 20 40 60 80 100 120 140 160D istance along flight line (east to west), km

F I G U R E 5-25.—Comparison o f r emote and in situ meas urement s fo r chlorophyll-a along a f l igh t l ine ( f rom ref . 5-18).




remote ly sensed E R E P da t a on the predic t ion mode l sw as nex t de te rmined . A l though c loudines s in the areaprec luded the use of cer ta in sensor da ta , the SI 92 da ta

were processed and the radiance values from bands 1 to7 and f r om b a nd 13 were used for the cloudless areas inth e original test regions . T h e i n f o r m a t i on c on t e n t o f

b a nds 4 and 5 was e l i m i n a t e d .The f ina l predic t ion mode l for whi te mar l in for onepar t i cu l a r d ay based on a S k y l a b pass over th e areay ie l ded a correla t ion coefficient of 0.892 (compared to0.489 without space data) a nd wa s s ignif icant at the 90-

percent level (as compared to the 60-percent level) .These resul ts , though based on l y on data for 1 day a ndon a subset of the tota l area t ha t w as inc luded in the pre -d ic t ion mode l , were fur the r eva lua ted us ing a mode ldeveloped from th e s a m e sur face - t ru th pa ramete rs tha twere used in the p r e v i ous m ode l , except that only thosetest areas for wh ich S192 data w ere avai lab le we re used.It w as c onc lude d , t he re fore , t ha t th e increase in preci -

s ion of the model could be a t t r ibuted to the data fromth e S I 92 sensor . O t he r aspects of the prob lem, such ast r y i n g to remove the e f fec ts of su ngl in t by d i f fe renc in gthe measurements made in the d i f fe re nt bands , were in -vestigated; th e effort w as unsuccessful.

The a pp l i c a t i on of these t echniques to larger areas ofth e ocean on a rout ine bas is to i m p r o v e th e efficiency ofthe variou s U.S . f ishing fleets wi l l not be achieved in thenea r fu ture . However , t h i s exper im ent demon s t ra tedth e feasibi l i ty of a t echnique tha t may eventua l lybecome ex t rem ely usefu l to the f i sh ing ind us t ry .

Coastal W ater In te rpre ta t ion

A s demons t ra ted b y their reports , th e P r i nc i pa l In -vest igators w h o used th e E R E P d a t a a re pioneers ins tudy ing potent i a l techniques for imp roved unders tand -

in g of the coasta l waters around cont inents and is lands .A typica l ma rine scient is t condu cts research fromsmal l , wel l -equipped coas ta l vessels f r o m w h i c h he ac-q u i r e s po i n t m e a su r e m e n t s such as ca tching f ish , net-t ing va r ious k inds of p l ank ton , de te rmining chemica lan d nu t r i e n t c on t e n ts of the water , a nd measur ing cur -rents. Th e problem with th i s approach is t ha t i t is notposs ible to cover a large area in great deta i l , anddiff icul ty is enco untered in rela t ing one set of m easure-ments t aken at one t ime and one place to a no t he r set ofmeasurements ob ta ined a t a di f fe rent t ime and ad i f fe ren t place.

A signific ant aspect of the S kylab missions is t ha t th ecoasta l imagery obtained can be used in many dif ferent

wa y s to aid in the i n t e r p r e t a t i on of the c onve n t i ona lda ta obtained b y m a r ine scientists. Th e methods

deve loped in the E R E P P r og r a m p o ten t ia l ly may a idm a r i n e scient is ts in their s tudies .

E i g h t P r i n c i p a l I n v e s t i g a t o r s a p p l i e d p h o t o i n -t e rp re t a t i ve t echniques such a s s t e reoscopic v iewing ,dens i tomet r i c ana lys i s , and c o l o r e nha nc e m e n t toEREP imagery to s tudy many coas ta l and oceanic

features. The areas s tudied were Chesapeake Bay byNicho l s (ref . 5-12) and Gordon and Nich ol s ( re f . 5 -13);Delaware Bay by Klemas et a l . ( ref . 5-22); the SetoNaika i , or In l and Sea, and other w a te rs a rou nd Japan b yM a r u y a s u et a l . ( ref . 5-23); New York State waterresources (L ake Onta r io and C onesus Lake) by P iech e tal. (ref. 5-24) (sec. 6 of this report); San Francisco Bayand Californ ia coasta l waters by Pir ie and Stel ler ( ref .5-11); Puerto Rico w aters by Tru m bu l l ( ref . 5-8) ; Block

I s l and Sound by Yost ( ref . 5-25); and the Gulf S treamby M au le t a l. ( re f . 5 -26) .The southern Chesapeake Bay , inc lud ing the Rap-

pahannock Es tua ry ( re fs . 5 -12 and 5-13) , is an area richin oysters and f ish and with rela t ively mild condi t ionsof t ide and r iver in f lo w. The t ides in such an es tuarycause marked changes in the amount of suspendedmateria ls tha t are indica ted in c i r cu la t io n pa t t e rns . Forexample , when the wa te r f rom the lower pa r t ofChesapeake Bay ente r s t he Rappahannock , i t can con-cent ra te on one s ide of the es tua ry and leave th e others ide untouched . Th e t idal currents produce smal l -scalem i x i n g pa t t e rns cont ro l l ed by changes in the shape andthe w idth of the es tuary. In t hi s inve st igat ion , S190Aand S190B da ta were ana lyzed w i th dens i tomete rs andfour dif ferent es tuarine water types were mapped thatwere rela ted to the water t ransparency, tu rb id i ty , andsuspended-sediment load . I t was possible to locatesmal l -scale mixing pat terns caused by local tidal cur-rents .

In the D e l a wa r e B ay s tu dy (ref . 5-22) , surface t ru thobtained from boats included measurements of Secchid e p t h , s u s p e n d e d - s e d i m e n t c o n c e n t r a t i o n ,t ransmis s iv i ty , t empera ture , s a l in i ty , and water color .In this investigation, emphasis w as placed on coastall and use and vege ta t ion m ap pin g a s prepa red f romE R E P p h o t o g r a p h s a nd SI92 scanner imagery . Thesepr od uc ts were used to m ap , at a scale of 1 :125 000, 10l a nd u s e a nd v e ge t a t i on c a t ego r i e s t ha t in c l u de ddel ineat ion of the we t l ands . A pa r t i cu la r ly va luab le




F I G U R E 5 -2 6 .—Aer ia l pho t o g ra ph o f red- t ide pattern observed in

the Sea of Bingo, Japan.

F I G U R E 5-27.—Enlargement of S190B photograph showing red- t ide

pa t te rn s (a r ro ws) in the Sea of Bingo, Japan (SL4-89-398).

aspect of the image ry was dis cr im inatio n of small dis-persed areas of marshland tha t a re part icular ly i m p o r -tant in the estuarine food chain. W i t h regard to themar ine s tudies , i t was possible to m oni to r su spe nded -sediment concentra t ions , to m ap su r face -cur rent c i r -cu la t ions , to locate boundaries of internal sys tems, tot rack surface sl icks, to follow ocean-waste dispersion,

and to monitor sh ip traffic.In studies o f data obta ined d urin g a pass over Japan ,Maruyasu ( ref . 5-23) used th e different colors in thewater on a single S190B photograph to trace the t idalcur rents in the I n l a nd Sea in the vicini ty of Koj ina Bay.A coinves t iga tor (Och ia i ) ana lyzed S190B ph otographsof the Sea of Bing o from the same Sk ylab pass and h igh-er resolution imagery from an aeria l multispe ctra l scan-ner to map the bound aries of indu str ia l eff luen tsaround the coasta l industr ia l zone and to detect oilpollut ion. An area of red t ide w as detected in the aerialpho tog r a ph and in an enlarged portion of an S190Bphotograph . As desc r ibed by Och ia i , "The mon i tor i ng

of the red t ide is considered [ to be] the most im po rtan ttask for f ishery [scientists] ."The yellow-colored vortexin figure 5-26 is one red- t ide pa t te rn tha t w as sighted inthe Sea of Bingo du ring the observation fl ight on Janu-

ary 11, 1973; it was also ident if ied in an enlarged S190Bphotograph ( f ig . 5-27).

Cal i fornia is an exce llent coastal area fo r demonstra t-in g th e po te n t i a l of use of low-Ear th-orb i t sensorsys tems fo r s tud ying coas tal and es tua r ine processesbecause of the varied types of features that are encou n-tered. The northern coast is rocky wi th sil t- laden

s t reams and r ivers. The southern coast has long, sandybeaches wi th eroding coasta l bluff forma t ions . Thestreams and r ivers of southe rn Ca l i fornia are usual lyd ry d u r i n g th e sum m e r m on ths . In San Pablo Bay,w h i c h is in the nor the r n pa r t of San Francisco Bay , sedi-me nt tr ans po rt was traced to areas of know n depositionwith Skylab imagery and was correla ted closely withplots of sediment di s t r ibut ion obta ined dur in g the sameperiod by ship surveys ( ref . 5-11).

Color-comp osite enhanc emen ts of S192 imag ery(bands 4, 6 , and 7) provided deta iled current and sedi-ment trans po rt patterns. The br ightness in the image ispropor t iona l to the amoun t of suspended se diment . The

sediment can be seen to flow southward pas t A lca t razIsland into South Bay. Some of this sedim ent a lso f lowsunde r th e Golden Gate Bridge and can be seen as ab o u n d a r y far out to sea. An S190A black -and -w hite




.F IGURE 5 - 2 8 . —E x am p le of discharge of sed iment - laden watersf rom th e Carq u i ne z Strait and the d i s t r i bu t i on in San Pab lo Ba y i nan S190A photograph (SL4-77-071).

pho tograp h of San Francisco Bay i l lustrates the var ia-tion in the sedim ent load (fig. 5-28).

The p a t t e r n s of dredged sediment discharges were

plotted over a 3-month per iod. I t was found tha tl i thogenous par t ic les , kept in suspension by the f resh-water f rom the combined Sac ramento and San Joaqu inRivers , were transpor ted downstream to the es tuar inearea at vary ing r a tes depend ing on the r iver -d i schargelevel . To measure th e t ranspor t in San Pablo Bay,dredged s ed i men t s were marked with ir idium beforedischarge near th e Carquinez Strai t . For May, June , andJ u l y 1974, th e m o v em en t s of these tracer sedimentswere plotted af ter col lec t ion and processing by 82 sta-t ions w i t h i n th e bay . Th is in fo rmat ion matched th em o v e m e n t s pred ic ted f rom in terp re ta t ion of EREP im-agery and pho tographs .

Th e pho tographs of San Francisco B ay were takendur ing a per iod of exceptional ly high f reshwater andsuspended-sediment discharge. A three-pronged surface

sediment pat tern is vis ib le wh ere the Sacramento-SanJoaquin River en ter s S an Pab lo B ay th rough th e Car-quinez Strai t . The th ree prongs exten ded to areas wh erem a x i m u m depos i t ion his tor ical ly occur s—the cen t r a lcha nnel , the southeast shore nea r Pinole Point , and th en o r t h w es t flats near the Peta luma River mouth . TheS190B color photog raphs were exc el lent for spectral andspat ia l resolution. Spectral analy sis of the pho tograp hsi nd i ca t ed t h a t th e sediment ref lec t ion peak w as near0 .55 f j .m. Nor thwes ter ly wind w as moving su r f acewaters into the southeast bay near Pinol e Poin t .

The SI90 photograph and others were processedus ing n a r r o w - b a n d filters and a dens i tometer , so as toproduce contours of suspended-sediment load as shownin figures 5-29(a) and 5-29(b ) . A suspensate concentra-t ion of a p p r o x i m a t e l y 2 mg/l i ter is qui te suff icien t to taga surface-current system and, by using progressivelylonger waveleng th f i l t e rs , th e sur f ace s t ruc tu re of cur-rents w i t h more th an 250 mg/ l i ter can be imaged.

M ea s u r em en t s of the suspended-sediment load pass-in g t h r o u g h th e Carqu inez S t r a i t on J a n u a r y 26 , 1974,were made. In the center of the channel , the concentra-t ion was a p p r o x i m a t e l y 25 0 mg/l i te r . A total of approx-imate l y 6.3 mil l ion metr ic tons of mater ia l passed intothe San Francisco Bay duri ng the 1973-74 season.Analys i s of the S190A photographs indicates a reflec-tance sh if t toward the green f rom the b lue as sedimentload increases. This sh if t ex p l a i n s th e excel lent detai l inth e 0.5- to 0.6-/u.m and in the 0.6- to 0.7-/i.m bands.

Dredging may be required in the Berkeley Flats areaof San Francisco Bay. Use of satel l i te and aircraf t infor-mat ion in this respect w i l l be benef ic ial , because th esites of shoa l ing and depos i t ion are detec table. Cos t sav-

ings us ing EREP- type da ta would vary wi th th e place-me nt and the e xten t of required dredging, but i t is possi-ble that savings of several mil l io n dollars could resul t .The technique s outl ined in reference 5-11 should be ap-pl icable for coastal and estuarine processes studied inother areas of the wor ld .

Exce l l en t EREP pho tographs were ob ta ined fo r thes t udy of the coastal processes and waters surroundingPuer to Rico (ref . 5-8). The study of these p h o t o g r a p h sy i e ld e d i n f o r m a t i o n c o n c e r n i n g m a n y i m p o r t a n taspects of the region. The important feature shown infigure 5-30 is the large anomalous blue area, which isa l s o ev i d en t i n f o u r o f t h e s i x f r a m es o f a

simultaneously obtained set of S190A photographs.This intensely dark blue, almost b la ck, area occupiesmuch of the Bah ia de M ayag iiez (approx imate ly 70

2 2 6 S K Y L A B E R E P IN V E S T I GA T I O N S S U M M A R Y



1 = M ax imum sed iment

9 • Minimumsediment

( a )

1 -M ax imum sed iment

9 = Minimum sediment

(b)

F I G U R E 5-29.—Con tour plots of suspended-sedim ent loads in San Pablo and San Francisco Ba ys , (a) 590 (±10) nm f i l t e r , (b) 490 (±10) nmf i l ter .

k m 2 ) and i s mos t s trongly developed o f fshore f rom theci ty of Ma ya gU ez , in and d o w n w i n d of an area of k n o w ndischarge of oily wa s te wa t er f r om t una p a c k i n g p l a n t sand other industr ies . Th e b o u n d a r y o f th i s deep-b lue

area on the south coincides with th e locat ion o f a reefedge; de p t h s in the l ighter colored area to the south aregeneral ly in the range of 5 to 8 m, wh ereas d epth s in thedeepest blue area are a p p r o x i m a t e l y 183 m . The in ten-

sity of blue in the dark -blu e area is clear ly not a s implefunct ion of depth , because nea rby deeper areas are notn ear ly as blue. I t seemed e v i de n t t o T r um b u l l th a t t h i sdeep-blue area w as caused b y some e f f luen t on the

wate r surface that changed the spectra l reflectance. Thepresence of the anomaly was unknown before the

E R E P s t udy .




Scale, km

F I G U R E 5 -30 .—Skylab 2 S190B color photograph of coastal w at e r s

of f wes t e rn Puer to R i c o (SL2-81-240).

A m o n g th e conclusions of the study were th e fo l low-ing. Th e synop t ic na tu re of the EREP informat ion per -

mitted the detec t ion and study of phenomena impossi-b le by any other exist ing technique. Th e S190B photo-g raphs con ta ined incomparab le ba thymetr ic de ta i l inw h i c h d ep t h s to a maximum of 26 m can be seen inareas of clear water. Th e turbidity of coastal w aters nearPuer to Rico is commonly high, reducing water penetra-t ion severely or el im ina ting i t entirely . However , depthcontours could be produced for cer tain areas .

T r u m b u l l concluded that Skylab- qual i ty data havepar t i cu l a r l y h igh po ten t ia l fo r studies of b a t h y m e t r y ,patterns of coastal currents, coastal erosion, sedimentt r anspor ta t ion and accumulation, effec ts of coastalworks o f man, and oil -s l ick detec t ion in the less well

developed coastal areas of the world. Coral reefs an dareas of coastal erosion were detected from orbitalp h o t o g r a p h s . P o t e n t i a l l y e c o n o m ic q u a n t i t i e s o foffshore deposits of sand, gravel, and mixed sand and

gravel were readily detec table on orb i ta l pho tographs of

S190 qu a l i ty , where bottom ref lec tance can be seen.Fie ld examina t ions a re required fo r accurate dif feren-t iat ion assessment of the resources.

Current s can be s tud ied in turb id coastal w ater . (Adisadvantage is that , because of c u r r en t va r ia b i l i ty in

t i m e and space, f requent coverage is necessary .)Eff luent discharges and oi l slicks of r e la t ive ly smal ldimensions are readily detec table. Large, dif fuse dis-charges, po tentia l ly dangerous ecologically , can bedetec ted and studied by means of orbital photographs.A l imi t in g r eq u i r em en t fo r oil -s l ick detec t ion seems to

be tha t the s l ick must not be in the Sun- azim uth direc-t ion f rom the center of the photograph.

Pho tographs of S190B qu a l i ty can por t r ay th e pat -t e rns and boundar ies of bo t tom-dwel l ing p lan t andan imal co mmu n i t i e s in clear water . It is, however ,necessary to m a k e a field check because these patternsare somewhat diff icul t and sometimes impossible to

d i s t i n g u i s h f r o m b a t h y m e t r i c p a t t e r n s . A l t h o u g hstereoscopic effects can be seen in the Skylab photo-graphs, they are not strong enough to show the app arentrelief of ba thy m etr i c features . Techniques such as thoseprev ious l y discussed are therefore preferred, as com-p a r e d t o a t t e m p t i n g t o c o n t o u r d e p t h s f r o mstereophotographs. A n impor tan t po in t , however , isthat the depth of the water can ac tual ly be seen f romspacecraft a l t i tudes in stereopsis. Both aircraf t andspacecraft p h o t o g r a p h s can be used to identify problemareas and to guide f ie ldwork from research vessels in amore in tel l igent w a y .

In an investigation of Block Island Sound and adja-

cent New Y ork coastal waters (ref . 5-25), pho tograp hictechniques were used that great ly enhanced subtle low-br ightness water detai l . Photographic contrast-s tretch-in g t echn iques app l ied to S190A photographs enableddifferentiation between tw o water masses having an ex-t inct ion coeff ic ient dif ference of on ly 0.07. B y dig it iz ing

S190A mul t i spec t r a l da ta in r eg is t r a t ion , a non-homogeneous ver t ical s trat if ic at ion of Block Is landSound waters with dif ferences in suspended sol ids of 1mg/l i ter was detected. Signif icant dif ferences betweenc onve n t i ona l t idal -current char ts and the ac tual pat-terns of w a t e r f l o w in Long Island Sound were estab-l ished. One such d if ference is the ex istence of two large

counte rc lockwise gyres heretofore undetected. Th eaverage extinction coeff ic ient fo r whi te light w asmeasured by ship at Block Island Sound to be 0.335,wi th a value of 0.400 for the blue band and of 0.554 for




t he red band. These opt i ca l wa te r cha rac te r i s t ics of non-homogeneous sur face and subsurface wa te r can be

cha r ted . Es t ima tes of suspended part icles larger than 5

/z m can be m a de .Both this sect ion and t ha t on f i she r ies indica te tha t

ma r ine s c ient i s ts could prof i t a b ly use imagery sys tems

such as those on the Landsat sa tel l i tes bu t w i t h th espectral bands specially selected to provide h ighspectra l resolut ion and information in the violet , blue-

green, and ye l low por t ions of the vis ible spectrum , p lus

one red b a nd . For these bands , th e effect of the at-m os phe r e is i m p or t a n t b e ca use th e l ight f rom th e imageis scat tered more and, he nc e , is a t t enua ted . However ,the many theoret ical analyses in these reports and in

th e s t udy of aerosols show promis ing t echniques tocompensa te for the in te rvening a tmosphere . Th e s ignal -to-noise ra t io of the p ar t icu la r bands in the spacecra f tsensor m ay stil l b e a l i m i t i n g fac tor . The prob lem re -m a i ns of re l a t ing a series of images , often obtained

m a ny weeks apart , to po i n t measurements m a d e b yconvent iona l techniques to relate th e t ime va r ia t ions a tselected points to the image over an extensive area . The

images can serve to assess th e problem and identify

po i n t s a t wh ich measurements w ould be needed.

ATMOSPHERIC PROPERTIES

Some of the energy that drives th e global at-mosph er i c c i rcu la t ion i s provided by evapora t ion ofwater from th e ocean surface. The Sun is the p r i m a r ysource of evapora t ive energy . The water vapor is

t r ansfe r red by vert ica l a i r cur rents t h rough the bound-ary layer , condenses, and produces c louds and l a t en theat. Thus, th e la tent heat of condensa t ion is a d r i v i ngforce of a tmospher i c c i rcu la t ion , p ar t icu la r ly at thelower la t i tudes .

Further advances in m a n ' s unde r s t a nd i ng a nd abil i ty

to predic t requi re a greater knowledge about th e radia-

t ion t ransfer through th e a tmosphere , th e sea-surfacetempera ture pa t t e rns , th e vert ical a n d hor izonta l windfields a t different a l t i tudes , and the physical ther-m od y na m i c c ha r a c t e ri z a t ion o f clouds .

Radiat ion Transfer

In addi t ion to the need fo r i m pr o v i ng k nowl edge o fthe physics of solar and terres tr ia l radia t ion t ransfer

through the a tmosphere , i t i s of ma jor impor tance tha tbet ter techniques be developed to correct for the effectsof a tmospher i c a t t enua t ion . Th e Sky lab m eteorologica lprogram placed ma jor emphas i s on the s tudy of rad ia -t ion t ransfer .

The a t m os phe r e is composed of dry gases ( n i t r oge n ,

oxygen (O 2) , argon, carbon dioxide (CO 2) , and tracegases), water vapor (H 2O ) , and aerosols. Because in -coming so la r rad ia t ion and outgoing t e r res t r i a l rad ia t ion

i n t e r a c t w i t h t h e s e a t m o s p h e r i c c o n s t i t u e n t s , t h et ransmiss ion of the beam is select ively modified as af u n c t io n of wavelength because of the spectra l nature ofth e i n t e r a c t i n g m e c h a n i s m s . R a d i a t i o n a t some

wavelengths is absorbed by gas molecules ( remova l ofphoton s f rom the beam) , whereas rad ia t ion a t o the rwavelengths is refracted or scat tered by molecules andaerosols. Total a tm ospher i c ex t inc t ion , the re fore , is theresul t of the combined a t t enua t ion due to scat teringplus absorpt ion .

A t m o s p h e r i c t r a n s m i t t a n c e m a y b e de f i ne d a sT = e ~ r , where T is the a tmospher i c opt i ca l depth . A no p t i c a l depth of 1 .0 impl ies an e x t inc t ion tha t wou ld oc -cur in an equiva lent ve r t i ca l pa th through th e mass ofth e clear a tmosphere. Figure 5-31 s h o w s th e re l a t ion-sh ip be tween a tm osph er i c t ransmis sion and wave lengthfo r the spectra l inter val covered by the S192, exc lud ingth e t he rma l inf ra red . In the vis ible region of thespectrum is a s l ight am oun t of absorp t ion caused by

ozone (O 3) at the shor tes t wave lengths . However , th emost i m po r t a n t a t t e nua t i on m e c ha n is m s are those d ueto scat tering by the gaseous ( inc lud ing water v apo r)molecules and aerosols.

C ha ng and Isaacs (re f. 5-27) measured th e a t t enua teddirect solar beam on the Great Sa l t Lake Deser t , U tah ,dur ing the Skylab pass on J u n e 5, 1973. Figure 5-32 il-lustrates th e spec t ra l modi f i ca t ion of incoming so la rradia t ion . Th e reduced solar intensi ty that reaches th egroun d i s ava i l ab le for evapora t ion and wa rmin g of thesurface, and some m a y b e back-reflected to space by thesurface. This back -reflect ion produces ph otograp hs andsignals for the S192, and the a tmospher i c e f fec t has oc-cur red o n both th e incom ing so la r beam and the ex i t ing

reflected beam.Th e absorpt ion an d sca t t e r ing func t ions for the dry

gases in the a tmosphere are genera l ly we l l known

(Rayle igh sca t t e r ing) . Ex t inc t ion b y wate r vapor , l iqu idwater , and ice crys ta ls (ci rrus) is not as wel l unde r s tood ,even though this factor appears to be of major impor -tance in the hea t ing and cool ing of the a tmosphere as




- V i s i b l e - - N e a r i n f r a r ed -

l . O i -

•

.(

. :

Cont inuum level due to scattering

P lo t ting resolution, 2 5 0 c m

, : .;• .8 .9 1 .0 1 . 2 5 1 . 6 7 .1

W a v e le n g t h , ^m

FIGURE 5-31. — Rel a t i o n sh i p b e t ween a t m o sphe r i c t ra n sm i ss io n an d w a v e l e n g t h for the spectra l in terval from 0.4 to 2.5 /um ( f ro m ref.5-27).

well as in l imi t ing the acc uracy of remo tely sensing cer-ta in Earth surface features. Th e ex t inc t ion of energy isexpressed in terms of optica l depth.

Aerosol laye rs may be composed of dry haze, wa ter-coated solid p ar tic les , or ice crysta ls. Sources of aerosolsin the a tmosph ere a re numero us and inc lude volcanice rupt ions , windborne so i l pa r t ic les , indus t r ia l anda i r c r a f t p o l l u t i o n , i n s e c ts , p r o t o z o a a n d o t h e r

microorganisms, and dus t of extrater restr ial or ig in . Thepa r t ic les usua l ly va ry cons ide rab ly in size , shape,c he m ic a l c om pos i t i on , and opt ica l cha rac te r is t ic s . In ad-d i t ion , aerosol layers are a lmost n ever hom ogeneou s ineither the vertica l or the horizonta l planes. In the a t-mosphere , an aerosol layer changes the radia tive bal-

ance and produces both hea t ing and coo ling effects. Theaerosol b acksc atter of inco mi ng solar ra dia tion in-creases th e to ta l Ea r th -a tmosp here a lbedo, whereas th eabsorption of solar and terrestr ia l radia tion increases

the a tmospher ic tempera ture ( and thus reduces the ne tr ad ia t ive cool ing) . Th e aerosol num ber den s i ty , pa r t i -c l e -s i ze d i s t r i b u t i o n , a n d l o c a t i o n w i t h i n th e a t -mosphere may be of s ignif icant inf luence on the

I

:

t

. :

absorption

band+

Scattering continuum—

H20

absorption

bands

Solar i rradiance

Solar beam attenuated by

summe r midlatitude atmo sphe re'

Solar elevation angle, 61.5°

O G round truth, pass 5

G re a t Salt Lake Desert , June 6 ,1973

Solar elevation angle, 62.96°

.4 .5 .6 .7 .8 .9 1.0 1.25 1.67 2. 5W a v e l e n g t h , ( i m

FIGUR E 5-32.—Atmospheric effects on incoming solar radia t ion

( f rom ref. 5-27).




F I G U R E 5-33.—Sequence of moonset p h o t o g r a p h s (35 mm) ob-

t a i n ed b y Skylab.

s t rength of the a t m os phe r i c c i r c u l a t i on . E i gh t S kylab in -

ves t iga t ions were devoted e i the r p r i m a r i l y or in part toi m p r o v i n g u n d e r s t a n d i n g o f vis ib l e an d inf rared rad ia -

t ion t ran sfer throu gh aerosol lay ers (refs . 5-6 and 5-27to 5-33).

P h o t o g r a p h i c exam ples of the resu l t s of a tm osp her i ca t t e n u a t i o n , re f rac t ion , and mo lecula r s ca t te r a re seenin figures 5-33 and 5-34. In figure 5-33, th e f u l l M o o n isseen set t ing beyond th e Ear th l imb. Th e dis tort ion ofth e M o o n in the bot tom f rame resul t s f rom ref raction

of the backscat tered-reflected solar energy from th e

M oon t h r ough th e Ear th ' s a tmosphere .Exce l l en t examples of the manner in which the

w h i t e l igh t of the Sun i s re f rac ted in to i ts com pon entcolors are shown in figure 5-34, two series of photo-graphs of the Ea r th l i m b as the Sun r ises above (f ig.5-34(a)) and sets below (fig. 5-34(b)) th e h o r i z o n . Thered co lor pred om ina tes in the mo re dense por t io n of thea t m o s p h e r e b e c a u s e a l l o t he r c o l o r s o f s h o r t e rwave lengths have been a t t enua ted ; tha t is , scat tered orabsorbed . As the molecula r dens i ty decreases w i th

he ight above the E ar th ' s sur face , t he rem ain ing colorc om pone n t s a ppe a r , un t i l all colors are seen as w h i t el igh t . The b lue above the whi te l igh t is due to scat te ring

by th e las t remnants of the a tmospher i c molecules .W i th i n t he d i spers ion o f co lors , t he ho r i zo nta l l ayers

seen in fram es 4 to 7 (f ig. 5-34(a)) are ind ica t ive of largec ha nge s in the i n d e x of r e f r a c t i on . The values of theseindices of re f rac t ion and t he i r heights are s igni f i cantand need to be eva lua ted in the rad ia t ion- t rans fe r equa -

t ions. Futu re l imb -ana lys i s inves t iga t ion s a re expec tedto resu l t in mo re d e ta i l ed opt i ca l pa ram ete rs thro ughana lys i s of f o r wa r d - s c a t te r r a d i a t i on , u s ing t e c hn i q ue ss i m i l a r to those used by Tingey and Pot ter ( ref . 5-32)w i t h backsca t t e red rad ia t ion .

Stratospheric Aerosols

The res idence t ime of aerosols in the s t ra tospherehas been conserva t ive ly es t ima ted to be at least 18months . Because of the concern about poss ib l e chemi -

ca l a nd t h e r m ody na m i c c ha nge s r e s u l t ing f r om t herelease of aerosols into the s t ra tosphere by man, manyefforts have been made over th e past decade to deter-mine ae rosol d i s t r ibut ion . These ef for t s have inc luded

l i tera l ly h u n d r e d s of a ircraf t , rocket , and ba l loon f l ights

as wel l as ground-based sea rchl ight and laser measure-

ments .

Models based on these measurements yield typ ica laerosol opt ical depths of 0.5 for aerosols a t a l t i tudesabove 20 km wi t h p r ob a b l e va r i a ti ons as great as 5 to 10t imes t h i s a m oun t . A s t ra tosph er i c ae rosol opt i c a l dep th




(a )

2 5 5 0 7 5 1 0 0

Scale, k m

F I G U R E 5-34.—Sequences of sunr i se an d sunse t photographs (35 mm) obtained by Skj lab 4. (a) Sunrise (SU-200-7639 to SL4-200-7648).(b ) Sunset (SL4-19S-7315 to SL4-19S-7319).




(b )0 50

S c a l e , k m


of 2.0 has been shown to cause an er ror of several per-cent in class if icat ion of grou nd t a rge t s ( re f . 5 -32). Thu s ,both scien tif ic and p rac t ica l reasons ex i s t for the s tudyof the stratospheric aerosol layers.

The Sk ylab spacec ra f t usua l ly orb i t ed in a so l a r - ine r -tial mode . D ur in g these pe r iods , i t was poss ible to ob-

tain q ua n t i t a t i ve m e a s u re m e n t s of the sola r backsca t t e rof the Earth l imb (f ig. 5-35) to use in s tudying the dis -t r i bu t ion of aerosols in the higher a tmosphere. Tingeyand Pot ter ( ref . 5-32) developed techniques to use l imb-b r i gh t ne ss m e a s u r e m e n t s (by S190A, S I91 , and S I 92 ) tode te rm ine a t t enu a t ion coef f i c i ent s of haze l ayers in the

s t ra tosphere . B y r a t i o i ng th e coeff i c ient s of a t t e nua t i ondue to aerosols and to dry gases ( R a y l e i gh ) , t he y we r eable to show th e l oca t ion and r e l a t i ve m a gn i t ude of hazelayers . The resul ts for one S192 pass are s h o w n in figure

5-36 ; a t t enua t ion coeff icien t peaks a s soc iated w i th hazelayers measured by S190A ar e s h o w n in figure 5-37.

From this w ork , i t wa s ascerta ined that several aero-

sol layers could be i dent i f i ed and t h a t th e a t t enua t ioncoeffi c ient s could be eva lua ted qu ant i t a t ive ly . I t shouldb e noted , however , t ha t th e resul ts of t h i s s tudy werel imi ted by the po i n t i ng a c c u r ac y of the spacecraft sen-sor and the absolute cal ibrat ion of the radiometers . This

s tudy unques t ionab ly ve r i f i ed tha t the l imb-br ightnes st e c hn i q ue is useful fo r e va l ua t i ng th e panicula te con-

t e n t of the s t ra tosphere . Aerosol l ayers were noted at20-, 40-, 50-, 60-, and 67-km a l t i tudes . Layers at a p p r o x -imate l y 40,50, and 5 5 km a ppe a r to be more respons ive

to longer wavelengths (0.71 /u.m), whereas layers a t 59and 67 km are m or e easi ly detected in the bandpass cen-tered at a wave length of 0.53 / - tm . This a pp r oa c h can be

used wi th da ta f rom futu re orb i t ing p l a t forms to mon i -tor the changes and var ia t ions in the s t ra tosphere be-tween 10 and 70 km.

Tropospher i c Solar Radia t ion A t tenua t ion

From th e earl ies t days of aer ia l photography , it hasbeen kno wn tha t v i s ib le rad ia t ion a t t enua t ion in theE a r t h ' s a t m os phe r e is p r i m a r i l y caused by aerosol scat-tering. Pioneer wor k by Lord Rayleigh (ref. 5-34), M ie(ref. 5-35), and, later, Van de Hulst (ref. 5-36)

deve loped genera l concept s fo r descr ib ing th e scat teringof l ight f rom spheres . (A l though it is recognized thatmos t d ry aerosols and ice crys ta l s are not s phe r i c a l , th eequa t ions for t rea ting s ca tt e r ing from nonsp her i ca l pa r -ticles are not yet ava i l ab le . ) Th e deve lopment of the




0 50 100

Scale, km

F I G U R E 5-35.—S190A c o lo r - in f r a r ed pho to g r aph of solar backscat-

ter from the E a r t h l i m b (SL4-52-388). Scale is applicable to l i m b

portion o n l y .

.5,

.4

.2

35

Altitude, km

F I G U R E 5-36.—Profile of aerosol a t t e nua t i on i n t h e stratosphere a s

measured by the Skylab Multispectral Scanner ( f rom ref . 5-32). The

ratio o f a t t en u a t i o n c o e f f i c i en t s (betas) du e to aerosols an d to d r y

gases is s h o w n as a f u n c t i o n of a l t i t ud e . Ra t i o peaks indicate panic-

u l a t e layers.

u

' . . - •

1.4

;. .

•§

•5 1.0

.6

:

.22 0 2 2 2 4 26 2 8

Alt i tude, km

30 32

F I G U R E 5-37.—Profile of aeros o l a t t e nua t i on i n t h e stratosphere as

measured b y the Sk y l ab M u l t i s p e c t r a l P h o t o g r a p h i c C a m e r a ( f rom

ref. 5-32).

m a t he m a t i c a l basis for modeling the transfer of radia-t ion throu gh scatt er ing atmo spheres is reviewed in thevar ious EREP repor t s .

A p r i m a r y f u n c t i o n o f s o l a r r a d i a t i o n - t r a n s f e rmodels is to correc t for atmospher ic albedo to obtain

surface a lbedo . For the most par t , the exis t ing modelsare only theoretical constructions and thus have veryl imi ted ap p l icab i l i ty to remote sensing. To developoperational models , one must inc lude a syn thes i s ofradia t ion-t ransfer theory , su r f ace- r ef lec t iv ity charac -ter is t ic s , and an a ppro pr ia te a tmosp her ic desc r ip t ion .Th e fact that fe w operation al visible-spectrum transfermodels have been developed is under s tandab le for thefol lowing reasons. First, specialized types of accuratedata i npu t tha t a r e o f uncer ta in avai labi l i ty are r equ i r ed .Second, th e high costs associated with model computa-t ion t ime and g round- t ru th field measurements areoften disp ropo r t ion ate to the resources available. Third ,




many t r ansfer models fo r a tmospher ic co r r ec t ion a re

no t suff icien tly accura te to w a r r a n t th e a t m o s p h e r i c a t-t e nua t i on ca l cu l a t i on . In the last case par t i cu l a r l y , th edi sc repancy between theory and measurement r esu l t sfrom a lack of u n d e r s t a n d i n g of the phys i ca l c o m p l e x -ities of m u l t i p l e sca t te r ing , th e effects of var ia t ions in

c he m i c a l and phys i ca l proper t ies of the haze l ayer s , andth e lack of k n o w l ed g e of the d i s t r i b u t i o n of the hazelayers in space and t ime.

Sky l ab prov ided a u n i q u e o p p o r t u n i t y to mak e accu-rate compar isons of the resul ts produced by the scatter -in g models to high-qual i ty measurements . Th e S k y l a bC o n c e n t r a t e d A t m o s p h e r i c R a d i a t i o n P r o je c t

(SCARP) (Kuhn et al . , ref . 5-30) inc luded a major fieldprogra m designed esp ecial ly to obtain f ield and aircraf t

data tha t cou ld be used to test and compare vis ib le-rad ia t ion t r ansfer models th rough wet , d ry , c lean , anddir ty atmospheres . A dist ing uish ing feature of thes tudy was the use of an aircraf t to ob ta in a tmospher ic

aerosol data. In ad dit io n, spectral measurem ents weremade of the su r f ace a lbedo , and d i r ec t mea suremen ts o faerosol optical depth were also obtained. Th e u n i q u e se tof data col lec ted for this s tud y was considered represen-tat ive of a large range of v a r y i n g Ear th a tmospheres andsur face targets with Sky l ab , ai rcraf t , and ground-basedobserva t ions co l lec ted fo r a mar i t ime, humid a t -mosphere near Hous ton , Texas ; a c o n t i n en t a l , h o t , d rya t m o s p h e r e n ea r Ph o en i x , A r i z o n a ; a n d a c o m b i n a t i o ndry -a tmo sphere and low-Sun-ang le cond i t ion a t W hi teSands , New Mexico .

From th is s tudy , i t was concluded that s ingle-scatter -in g models are most sensit ive to aerosol- ref rac t ive- in-

dex i n p u t and that aerosol optical depth is a cr i t ical in -put for the more ref ined mul t i p l e - sca t t e r ing models . Ofpar t i cu la r in teres t and p rac t ica l impo r tance w as the ev i -d e n c e t h a t m o r e r e f in e d v i s i b l e - r a d i a t i o n - t r a n s f e rmodels are not i m p r o v ed by use of aerosol measure-men t s f rom a ircraf t . Only measurements of aerosol op-t ical dep th made a t the su r f ace a re needed to op t imizemodel accuracy . Fur therm ore , by mea n s o f t h e S C A R Pmea sureme nts , tech niques were developed to inver tm a t he m a t i c a l l y the su r f ace op t ica l -dep th measure-ments to obtain the aerosol-s ize-dis tr ibution function.

These two f indings are considered of m a j o r i m p o r t a n c efo r future remote-sensing ac t ivi t ies .

N u m er o u s S k y l a b i n v es t i g a t i o n s in f ie lds v a r y i n gf rom m i n e r a l ex p l o r a t i o n to oceanography inc luded a t-mospher ic co r r ec t ions to p r o v i d e m o r e a c c u r a t e infor -

ma tion on true surface albedo (e.g. , refs . 5-26 and 5-31).These inves t iga t ions , a l though in ter es t ing from th es t a n d p o i n t o f r a d i a t i o n t r a n s f e r t h r o u g h t h e a t -

mosphere fo r different airmasses and s lant ranges, werep r i m a r i l y d i r ect ed t o w a r d i m p r o v i n g t h e m ea s u r em en taccuracy of r emote ly sensed su r f ace phenomena .

Tropospher ic In f r a red Rad ia t ion At tenua t ion

In th e prev ious subsec tion , r ad ia t ion o r ig ina t ingfrom the Sun , which has a tempera tu re near 6000 K ,w as d iscussed . Rad ia t ion o r ig ina t ing f rom sources hav -in g t empera tu res o f usual ly less than 320 K is discussedhere in .

O n a wor ldw ide bas i s, an average of 27 percen t of the

direc t solar radiat ion a nd 20 percent of the energyreflected downward by o r conduc ted f rom the a t -mo s p h e re (or a total of 47 percent of the solar energyt h a t reaches the top of the atmo sph ere) is absorbed bythe Ea r th . The energy th a t i s no t used fo r evapo ra t ion

and pho tosyn thes i s hea ts th e surface and subsequen t lyis reradiated at infrared wavelengths f rom the surface.In s om e w a v e l en g t h s , it is absorbed by cer ta in cons t i tu -en t s of the a t m o s p h e r e , p r i m a r i l y c a rb o n d i o x id e ,

ozone, and water vapor , and thus heats th e a tmosphere .The c o m b i n ed effects of geograph ica l v a r i a t i o n s in sur -face t empera tu re and a tmospher ic absorp t ion d r ive the"a tmospher ic eng ine ." Measurements of the r a d i a t i o n

budge t componen ts f rom sa te l l i t es p rov ide da ta on theenergy budget o f the Ear th . These data comp r ise a p r i -m a r y i n f o r m a t i o n s o u rc e f o r n u m e r i c a l w e a t h e rforecast models . Hence, imp rove me nt in unde rstand-in g th e p h y s i c s of infrared ter restr ial radiat ion transfert h r ough the a tmosphere would d i r ec t ly con t r ibu te toimproved numer ica l models fo r global wea ther forecast-ing.

A smal l par t of the outgoing infrared rad iat ion or igi-nates at the surface and in the clouds and escapesth rough the a tmosphere th rough r ad ia t ion " wi n d o ws , "w h i c h are the spectral regions between the absorptionbands of the gases. I n f o r m a t i o n on var ious aspects of




100 r

F IGUR E 5-38.—Generalized atmospheric transmission in the in-

frared por t ion of the elec tromagne tic spectrum.

th e a t m os phe r e and i ts b e ha v i o r can be obta ined bymeasur ing th e u p f lu x of terres tr ia l radia t ion a t these

se l ec ted wave lengths . O f pa r t i c u l a r i m por t a nc e in the

measurement of c loud- top and Ear th sur face t em-pera tures i s the a tmospher i c wind ow in the 8 - to 12-^mregion of the in f ra red spec t rum. Because a tm osph er i c

gases cause l i t t le a t t enua t ion in th i s spec t ra l band ( f ig .5-38) and because the terres tr ia l rad ia t ion peak s in thisregion , mos t of the remote -sens ing measurements ofsurface t e m pe r a t u r e s fo r s tudies in geology , ag r i cu l ture ,oceanography , e t c . have been made in this spectra l in-t e rva l . U n f o r t u n a t e l y , even in the early days o f sa tel l i temeteorology , i t was noted that a t no place in the in-f r a r e d s p e c t r u m w a s t h e atmosphere c o m p l e t e l yt ranspa rent . Even in the 10- to 11-ptrn region , a s m a l la m o u n t of outgoing t e r res t r i a l rad ia t ion is absorbed by

t he w a te r vapor in the a tmo sphere . In addi t ion , a s ig -n i f i can t b u t u su a l ly unk now n a m oun t o f a t t e nua t i on oc -curs as the r a d i a t i on passes t h rough haze l ayers and in -

vis ible ci rrus cloud lay ers (ref . 5-37) . A s a consequence ,many cor rec t ions mus t b e made before rad ia t ionmeasuremen ts f rom Ea r th-orb i t a l s a tel li t es can bet r a n s l a t e d i n t o m e t e o r o l o g i c a l l y m e a n i n g f u l

pa ramete rs .D ur i ng th e past decade, numerous t heore t i ca l a n d

e m p i r i c a l model s have been developed to p e r m i tr igorous analy t ical deriv at ion of Earth surface andmeteorological data from infrared-sensor measure-ments. M os t models of inf ra red rad ia t ion t rans fe r

developed fo r remote -sens ing appl i ca t ions differ signifi-can t l y f rom one another in the man ner in wh ich the a t -mosph er i c t ran smis s iv i ty for the va r ious gases and pa r -t i cu la tes i s inc luded in the rad ia t ion- t ran s fe r equa t ions .

D e t e r m i n i ng th e accuracy a n d ut i l i ty of these modelsand inves t iga t ing the i r app l i ca t ion to the es t ima t ion ofc l o u d - t o p , l and , and sea -sur face t em pera tures w ere ma-

jor e f for t s of the ER E P Inves t iga t ions P rogram ( re fs .

5-8, 5-29, 5-30, 5-33, an d 5-38).One of the p r im ary ob j ec tives of SC A RP was to ob-

tain f ie ld measurements of the cri t ica l paramete rs usedin ev a lu a t in g these models . Surface, aircraf t , a ndb a l l o o n b o r n e sensors ob t a i ned p e r t i ne n t da ta unde r t he

Sky l ab spacecra f t a t targets in southeas te rn Texas a ndin t he Gu l f of M ex ico (m ar i t im e , mois t a irmasses) anda t W h i t e S ands, N e w M e x ic o , a nd P h oe n i x , A r i zona( c o n t i n e n t a l , dry a irmasses) . These da ta , toge the r w i t h

th e Skylab S191 m easurem ents , afforded bet ter ins ighti n to t he m e c h a n i s m s o f inf ra red rad ia t ion t rans fe rt h r o u g h t he a tmosphere , a s well as a s ta t is t ical com-parison of the accuracy of the t ransfer models in cur-rent use ( f igs . 5-39 and 5 -40) . The SC A RP inves t iga t ions howe d t ha t , whe n suff ic ient i n f o r m a t i o n is ava i l ab le ,

th e p r e se n t num e r i c a l m ode l i ng is adequate fo r predic t -in g t he t rans fe r of inf ra red rad ia t ion through the a t -m os phe r e w i t h an accuracy of a p p r o x i m a t e l y 1 K .

For mos t s tudies , how ever , anc i l l a ry da ta f rom sur -face, aircraf t , or bal loon measurements are not avai la-

ble. To e l i m i na t e th i s r e q u i r e m e n t , A nd i ng an d W a l k e r(ref. 5-6) developed a techn ique based on the use of thedifferent ia l opt i ca l proper t i e s of the a tmosphere in thein f r a r ed -win d o w region to infer t he a tmospher i c a t -t e n u a t i o n . They then used the a t t enu a t ion va lues to cor -

rect for the e f fec t of the absorpt ion of a tmospher i cgases on radiome t r i c da ta. As shown in f igure 5-41, the ydemons t ra ted tha t th i s method of ca l cu la t ing the

spectra l radiance a r r i v i n g a t the top of a ma r i t im e a t -mosphere compared qui t e favorably w i t h th e S191measurements . Th e agreement is excel lent in theb a ndpa s s e s f r om a pp r ox i m a t e l y 11 to 13 /u .m. Fo r t h i sevaluat ion, a 100-percent-mari t ime (wet) aerosol with23-km sea-level visibi l i ty w as assumed. To test the ap-p l ica t io n of th i s method of ana lys i s, t he in -b and br ight -ness t empera tures were computed an d plo t t ed aga ins trela t ive ext inct ion coefficients (f ig. 5-10) .

In addi t ion to the s ize , shape, and na t u r e of the aero-so l pa r t i c l e , th e effect of the degree of wetness mus t beconsidered. In the A n d i n g - W a l k e r s tu d y and in theS C A R P m a r i t i m e s t udy , th e aerosol part icles were

assumed to be water coated. Th e W h i t e Sands andPhoenix aerosols were assumed to be composed of dryquar t z . Exam ples o f t ransm is s iv i ty of ae rosol l ayersbased on these assumptions are shown in f igure 5-42.

23 6 S K Y L A B E R E P IN V E S T IG A T I O N S S U M M A R Y



60

•

ECL

100

• O R A D I A N V

D EXTC OEF

A Boudreau

0 R A D I A N C

V A i rc ra f t

1 kPa = 10 mb

l l O l

1000 N/m

286 288 290 292 294

Apparent surface temperature, K

2% 29 8

F I G U R E 5-39.—Modeled an d mea su red ( a i r c ra f t ) e a r ly - morn ingt empera tu r e p r of i l e s fo r Rosenberg , Texas, on August 9,1973 ( f rom

ref. 5-30).

v

I

iso

61

r o

•

-

100

O R A D I A N V(B i g n e l l continuum)

Q R A D I A N V(E lsasser continuum)

A Boudreau

O R A D I A N C

0 SI91

O A i rcra f t

1 kPa =10 mb -1000 N /m

300 305 310 315 3 20 3 25

Apparent surface temperature, K

330 335

F I G U R E 5-40.—Modeled an d mea su red (SI 91 and a i rc ra f t ) t em-pera ture profi les computed to the top of the atmosphere for RainbowVa l l ey , Arizona ( f rom ref . 5-30).

The op tical dep th of the aerosol laye rs was measured byaircraf t i n s t r u m en t s fo r SCA RP. W hen ac tua l measure-ments were no t ava i l ab le , assump t ions o f op t ica l dep thwere based on hor izon ta l vis ib i l i ty b y A n d i n g andW a l k e r (ref . 5-6), Maul et al. (ref. 5-26), Turner (ref.5-33), and others . The aerosol problem is f u r th e r com-pl icated because these layers are tenuous; that is , theychange almost continuously in composit ion, s ize dis-t r i b u t i o n , a n d l o c a t i o n w i t h i n t h e a t m o s p h e r e .A l t h o u g h t h e Sky lab EREP inves t iga t ions p rov idedhe lp fu l new data , th e prob lem of aeroso l a t tenua t ion ofboth v is ib le and in frared rad iat io n has not been solved.

Atmospher ic W ater , C louds , and Precipitation

W ater , because of its pecu l ia r r ad ia t ion -a bsorp t ioncha rac te r i s t i cs , its changes of state w i t h i n the normal

ranges of a tmospher ic tempera tu res , it s cap ab i l i ty to ab-sorb much of the heat radiated f rom the Ear th 's surface,and i ts large gradients of concentrat ion, both hor izon-ta l ly and ver t ical ly in the a tmosphere , is an i m p o r t a n tfactor in the energy budget of the a t m o s p h e r e and adominan t f ac to r in the produc t ion of weather events .Ear th-orb i t a l sa te l l i t es have p rov ided major new con-t r i bu t ions to knowledge of a tmospher ic water and havemade possible th e g loba l assessment of the quan t i t i es ,the fo rm s , and the d i s t r ibu t ion pa t te rns o f a tmospher ic

mois tu re as func t ions of t i m e and space.C louds are of major meteorological s ignif icance fo r

several reasons.

1. Clouds shield th e surface f rom a por t ion of thesolar radi at io n. Because of their high albedo, c loudsreflect m u c h of the solar energy back to space with th eresul t tha t areas below c louds are cooler dur in g day tim e.






wh ere the sha rp ly def ined wa te r c louds g ive way to thediffuse ic e crys ta l layers .

In addi t ion, i t i s often poss ible to i den t i fy areas ofs t rong convec t ion f rom shadows of tall c u m u l o n i m b u stowers (p a r t i cu la r ly under low-Sun-angle condi t ions ) .

Je t - s t ream c i r rus often cas t s shadows on lower c loud

decks , and th in , h igh c i r rus may be id en t i f ied by i ts in-f luence on the image of lower clouds . Satel l i te photo-g r a phs o f c loud pa t t e rns show tha t th e c loud e l ementsm ay be e i the r randomly d i s t r ibuted or organized in tosome regula r forma t ion . Such forma t ions a re n o r m a l l y

associa ted with o n e o r more a t m os phe r i c a nd / o rtopographic fac tors .

Because other satellite programs are dedicated to ob-t a in in g de ta i l ed informat ion on the s t a te of the a t -m os phe r e , th e n u m b e r of meteorologica l exper iments

on S k y l a b was l imi ted . The cap ab i l i ty of man to takehigh obl iqu e ph otogra ph s and s te reophotographs i su n i q u e , and the inform at ion ga ined by the Skylab c rew-

men's p h o t o g r a p h i c d o c u m e n t a t io n d e m o n s t r at e sforceful ly th e va lue o f manned space programs . Th eSky l ab 4 c rew acqui red s t e reophotographs of num erousclassical a nd unique c loud pa t t e rns , inc luding thun-de r s to r m s , t ropica l a nd ex t ra t ropica l cyc lones , mou n-ta in wave clouds , convect ion in cold a ir pass ing over

w arm w ater , je t -s t ream cirrus , is land vortex and con-vect ion effects , sea breezes, c loud streets, and sub-

synopt i c -s ca l e a tmospher i c c i rcu la t ions .The c loud-s t ree t or i en ta t ion seen in figure 5-14(a) is

an e x a m p l e of the m a nne r in which c loud rows are usedas an indicator of low-level win d f lo w in areas for which

radiosonde and surface meteorological observat ions are

not avai lable . Pi t ts e t a l . ( ref . 5-28) conducted a f ie ldprogram to obta in hour ly rad iosonde soundings concur -rent wi th photographic da ta for a c loud-s t ree t pa t t e rn

over Fort Sill, O k l a h o m a , in June 1973. They learnedtha t th e c loud-s t ree t or i en ta t ion conformed to the w i n dvector at the base of a t empera ture invers ion (c loud- top

he ight ) in th i s case.

Th e remote measurement of air m o v e m e n t a tdifferent a l t i tudes has been a t t empted by means ofvar ious t echniques ranging f rom measurements ofc loud-s t ree t or i en ta t ion to the sa te l l i t e moni tor ing ofth e m ove m e n t s o f constant-pressure bal loons .

In a no t he r e x pe r i m e n t , Villev iei l le and W ei l l e r (re f.

5-39) rela ted vert ica l -wind profi les with cloud-s treetparameters us ing satel l i te photographs . This s tudy pre-

sents th e t heore t i ca l deve lopment and a lgor i thms oft e c h n i q u e s f o r c a l c u l a t i n g i m p o r t a n t a t m o s p h e r i c

l . O O r

"

_•>

O W h it e Sands

D Phoenix

A Houston

11 12 13W a v e l e n g t h , p .m

FIGURE 5-42.—Transmiss ivi t ies due to aerosols c omputed from

EXTCOEF us ing the aerosol -s ize-dis tr ibut ion data col lec ted at threetest sites (from ref . 5-30).

stabi l i ty a nd wind-shea r parameters. Further discuss ion

of the methodology of ver t i ca l -wind-pro f i le ca l cu la t ionsis included in sect ion 6 .

In earl ier s tudies , Kuet tner (ref . 5-40) and L e M o n e(ref. 5-41) reported that th e range of the ra t io of thespac ing be tween th e hor izonta l streets to the he ight of

th e t empera ture invers ion was 2 to 4 . The E R E P da t aindicated that th is spacing ra t io was 1 .7 for the Fort Sill,

O k l a hom a , s t udy , wh i c h wa s sl i gh tl y less than the ra t iorange found in the earl ier s tudies .

Invest igat ions to describe cloud physical s t ructures

us ing c loud radiance measurements m et with va r iedresults . C ur r a n et al. (ref. 5-29) attempted to compare

th e cloud-top a l t i tudes measured b y us ing l l - / ^m the r -mal-infrared (S192 channel 13) radia t ion w ith those




Temperatu re

in te rva l , K

1 9 0 - 1 9 6

Ice cloud v-..

V

W ater cloud--"

Open area

F I G U R E 5-43 .—Computer-genera ted image of the t h e r m o d y n a m i cphase of wate r in an S192 cloud scene ( le f t ) as compared to the fa lse-

co l o r t he rm a l - i n f ra red i m a g e (m i dd l e ) , t he co l o r t em pera t u re sca lefo r whi ch i s sho wn a t r i g h t ( f rom ref . 5-29) .

us ing s te reoscopic t echn iques on S I90 photographs . Aqual i t a t i ve compar i son of c loud- top t empera tures wi ththe w ater phase of the c loud top is sho wn in figure 5-43

and indica tes tha t fu ture s tudies of th i s type can provideuseful meteorologica l informat ion .

S kylab E R E P i nve s t i ga ti ons c on f i r m e d t h a t i n f r a re dsensors on satellites tend to e i the r underes t ima te oroveres t ima te c loud- top a l t i tudes based on th e i r b l ack-body t emp era tures . High c louds (15 000 m) w ere under -es t ima ted by app rox im a te ly 1000 m and low c louds(3500 to 7000 m ) were overes t ima ted . These errors wereto be expected unless th e measurements were correc tedfo r gaseous and aerosol a t ten ua t io n, because even sma l ler rors in temp erature resul t in qui te large errors ina l t i t ude es t imates .

C urr an et a l . ( ref . 5-29) foun d th at the ra t io of cloud

reflectance a t wavelength 1.61 /urn to that a t wavelength0.754 ^m as a func t ion of the c loud op t i ca l t h i ckness at0.754 /Am can be used to di s t ingui sh between c loudsc om pose d of ice crys ta l s and those composed of l iqu id

.Liquid droplet

10 100

O pt ical thickness at 0 .754 M .

100

F I G U R E 5-44.—Rat io of cloud reflectance a t 1 .61 /xm to tha t a0.754 M m as a f u n c t io n of cloud opt ica l th ickness at the latte

w a v e l e n g t h . Bands are formed by two ext rem es in part icle-size d is

t r i b u t i o n , w i t h a sm a l l -pa r t i c l e d i s t r i b u t i o n (m ea n pa r t i c l e ra d i u s

= 4.5 Mm) f o r min g t he u ppe r b o u n d a n d a l a rg e -p a r t i c l e d i s t r i b u t i o n(r = 16.2 nm ) fo rm i n g th e l o wer ( f rom ref . 5-29).

drop lets (f ig. 5-44) . W hen app l ied to the m u l t i s p e c t r ascanner , appro pr ia te chan ne l da ta enab led de te rmin at ion of the t h e r m o d y n a m i c pha se of the cloud topsA l i s hous e et al. (ref. 5-38) and Pitts et al. (ref. 5-28) alsorat ioed reflectances in the na r r ow b a nds in the vis ib land nea r inf rared to d is t in g u ish between ice crys ta l andwate r drople t c louds .

S kylab E R E P e x pe r i m e n t s p r ov i de d s om e e v i de nc et ha t d isc r imin a t io n is poss ib le amon g c loud ic e crys ta l sc loud w a te r drop le t s , and su r face snow. However , t he

need ex i s t s to ex tend d i s c r i min a t ion to inc lud e supercooled water droplets , mixes of ice crys ta ls and waterdroplets , ice crys ta l s tabi l izat ion ( i .e . , agi ta ted inc u m u l u s top as opposed to t ropopause s t r a t i f i ca t io n )

and mixes of sur face snow crys ta l s t ruc ture s .Because of i ts spectra l reflec t ive and the rm al charac

te r is t ics , snow cover great ly affects both the energybudge t at the surface and the regional water balanceN ew advances in s now-c ove r m a pp i ng u s i ng S kylab

sensors are discussed in sect ions 4 and 6.

Soil Moisture

A l t h o u g h t he de te rmina t ion of so i l mois ture contenis nor ma l ly cons ide red in the rea lm of agr i c u l ture , t hemeteorologis t is interes ted in spat ia l and temporalvar i a t i ons o f soi l mois ture , pa r t i cu l a r ly in the first few




cen t imeter s be low the surface, because th e mois tu rec o n t en t of the surface soil s trongly inf luences soil ther -m al proper t ies and evapo t r ansp i r a t ion r a tes . Becausewa t e r has a greater specif ic heat than does m inera l so i l,fo r a given heat i np ut , mo ist surface soils will be coolert h a n d ry so i l s dur ing th e d a y .

M a r w i t z (ref. 5-42), Davies-Jones (ref. 5-43), andSasaki (ref . 5-44) have shown that th e inf low air sourcefo r severe thunder s to rms is from th e near - su r f ace l ayer

of the a tmosphere . Heat and mois tu re f rom the so i lt r ansfer r ed t h r o u g h t h i s inf low air p r o v i d e a d d i t i o n a lenergy to the s torm system. Beebe (ref . 5-45) repor tedthat the tornado f requency m a x i m u m s i n t h e T ex a sPanhand le were centered in a region of extensive irriga-t ion. He concluded that the increased water vapor sup-pl ied to these tornado c loud systems was a resul t ofe va po t r a ns p i r a t i on f rom th e irrigated f ie lds .

In theory a t l east , the use o f mic row ave f r equen c iesis a d i r ec t approach to the measurement o f so i l

mois tu re . W ater has a very h igh d ie lec t ric cons tan t ;soils have very low constants . Moist soi ls thereforeh a v e a dielec tr ic constant that is p r o p o r t i o n a l to therelat ive amounts of water , soi l , and air present .

The inf lue nce s of soil type , surface roughness, andv eg e t a t i v e co v e r o n m i c r o w a v e e m i s s i o n a re a l lwaveleng th dependen t wi th the s trongest effec ts at theshor ter wave leng ths ( r ef . 5 -28) . A s ign i f ican t advan tageof the longer waveleng ths is tha t m easurements a r e no trestricted to cloudless skies. A t L - b a n d ( a p p r o x i m a t e l y21 cm) waveleng ths , the a tmospher ic t r ansmiss ion i s

close to u n i t y w i t h l i t t le in f luence f rom c louds orgaseous absorbers .

Several s tudies were conducted to eva lua te th emicrowave L -Band Rad io mete r (S194) fo r soil moistured e t e r m i n a t i o n . These results are described in section 6.

Pit ts et al. (ref . 5-28) comp ared L-ban d mea surem entswith an i n d ex of an teceden t p rec ip i ta t ion for twoSky l ab passes across O k l a h o m a , N ew M ex i c o , andTexas. Th e an teceden t p rec ip i ta t ion index (A PI ) is as imple method of cha rac te r i z ing the p rec ip i ta t ion h is to -ry in w h i c h

It

API = (5-2)

i = \

230

• 24 0

f!250

•c 260.Q

§

" 2 7 0

28 0

11-day AP I

w h e r e /> / is the dai ly p rec ip i ta t ion fo r each day f rom n

days previous to the curre nt day / and K character izes

0 20 40 60 80 100 120 140

M easurement point

F I G U R E 5 -4 5 .—C ompar i s on of S194 L-band brightness temperature

a n d a v e ra g e 11-day antecedent prec ipi ta t ion index (API ) and 5-day

A PI fo r June 11 , 1973 , over southwestern Oklahoma an d n o r t h -eastern Tex as (from ref . 5-28). Th e l ac k o f correla t ion between th e

5-day API and L-band brightness t empera tu r es ind ic a tes t he

necessi ty of averaging precipi ta t ion for longer periods.

the loss of moist ure f rom th e soil due to evap otrans pira-t ion and deep perco la t ion and is a f u n c t i o n of soil type,slope, season, and vegeta t ion .

The an teceden t p rec ip i ta t ion index i s compared w i thS194 br igh tness tempera tu re fo r a Sky l ab pass acrosss o u t h w es t e r n O k l a h o m a and n o r t h ea s t e r n Texas infigure 5-45. From th e studies , it is conc luded tha t t he L-b a n d of the m i c r o w a v e is well suited fo r remote sensing

of synoptic soil moisture over large areas under a w i d e

variety of weather , vegeta t ion , and te r r a in cond i t ions .

M ea s u remen t of Sea-Surfac e W i n d s

Th e m a j o r purpose o f the r ad iometer - sca t te rometer( r ef . 5 -46) exp er imen t w as to ob ta in s im ul tane ousm e a s u r e m e n t s o f r a d a r b a c k s c a t t e r a n d p a s s i v em i c r o w a v e t e m p e r a t u r e s t o d e m o n s t r a t e t h a t t h epass ive mic rowave tempera tu res cou ld be used to cor -r ec t fo r a tmospher ic a t ten ua t ion and tha t the backsca t -te r mea s u remen t s , af ter correc t ion, could be used todetermine w indspeed and w ind d i r ec t ion .

The w ind s over the ocean surface are very diff icul t tomeasure. The windspeeds inc rease w i t h h e i g h t , and therate of increase depends on the d i f f erence in tem-pera tu re be tween the wa ter and the a i r . M oreover , the




10

:

O i n~

™ 1 0

f 10--

E|10I8 10"c-;

5 10

-

-

- 1 5 m / s e c

- 1 2 . 5 m / s e c

r— 10 m / s e c

\—7.5 m / s e c

I I I I I I I I

5 10

Frequency, Hz

50 L O O

F I G U R E 5-46.—Spectra of w a v e s that exist s i m u l t a n eo u s l y on aw a t e r su r fa ce wi th specified windspeeds (from ref. 5-47).

wind s are turbu len t and f luctuate about an averagev a l u e in both speed and direc t ion . Fo r im pr ove dn u m er i c a l wea ther predic t ion methods , the proper lyaveraged winds need to be measured on an oceanwidescale and on a un i f o r m g r id of points . Da ta ob ta inedf rom the S193 prov ided a sc ient i f ic b reak through in thefield of the meteorology of ocean w in d fields.

T h e w i n d s g e n e r a t e w a v e s o f a l l l e n g t h ss i m u l t a n e o u s l y o n t h e o c e a n s u r f a c e . T h e s e

wav elengths v ary from 0.6 cm to more tha n 600 m, withthe high est waves travel ing in the wi nd direction. Somewaves travel in directions that are ±90° rela tive to thewind direction. As the windspeed increases , waves o f alllengths grow in he ight .

Tha t th e he ight of high-f requency capi l lary waves in -creases with an increase in windspeed has been shownby measurements made by Mitsuyasu and Honda ( re f .5-47) in a win d- wa ter tun nel . This exper iment provides

h igh - f r equency - spec t rum data to support the theorytha t cap i l l a ry wave structure is a dominant fac tor inradar backscatter , and the data show a power-lawwindspeed dependence. Figure 5-46 shows that the

spectrum of the waves grows w i th windspeed in the 5-to 30-Hz frequ enc y range when observed as a func tionof t i m e at a po in t . Th e w inds in the tunne l for the fivecurves sh own had n om inal v elocity values of 5 , 7.5 , 10,

12.5, and 15 m/sec ; the curve for the 15-m/secwindspeed corresponded to 33-m/sec winds at an eleva-tion of 10 m above the sea surface.

Th e gr ow th in he ight of in te rmedia te - length wavesand the increasing roughness of the sea wi th increasingwindspeed are st r ik ingly i l lus t ra ted by a series of photo-

graphs taken f rom th e wea ther sh ip Papa wh ile s ta-t ioned in the N o r t h Pacific (ref. 5-48). The sea surfacebecomes increa singly rough as the speed of the w in d, asmeasured just above the surface, increases. The S193measured this increase in roughness and , a t i n c ide n tangles of 50°, 43°, and 32°, the radar backscatter thatw as measured for a given rela tive wind direction in -creased wi th windspeed. The measured radar backscat-ter was correla ted both theore t ical ly wi th sea-surfaceroughness and winds ( ref . 5-49) and direc t ly wi th th ewinds by means of mu ltiple-reg ression techniqu es ( ref .5-49). Sea roughness is de pe nde n t on both wind d i rec-tion and windspeed . The Sky lab results de mo nstra t e

tha t , if the wind d i rec t ion is k n o w n from an i nde pe n -dent source, th e windspeed can be de te rmined from th ebackscatter measurement. The Advanced Ap pl ica t ion sFlight Ex pe r im e n t s ( A A F E) L a ng l e y R a dsc a t P rog r amshowed t ha t , as the windspeed increases by a factor of 5,th e backscatter increases by more than a factor of 10( f i g . 5-47).

Fung and C h a n ( in ref. 5-49) succeeded in using th espectra l form for the capi l lary waves shown in figure

5-46 and the ava i lab le i n fo rmat ion on the slopes of thelonger waves (pe rhap s 10 m long an d longer) to der ive acomposi te theory fo r backsca t te r . Th e large-scale w a v y

surface w as tilted back and for th ( in theory) , and the

backscatter f rom th e sma l l waves, whic h were app rox -imate l y 2 cm long, w as ca lcula ted for the dif fe rentslopes and s u m m e d over th e slopes. A typica l r e sul t isshow n in figure 5-48, w he re th e parameter a 0 describesth e angular spread of the capil lary wave spec t rum.

Three methods were used to de te rmine the wind-f ield paramete rs which were cor re la ted wi th th e S193data. For Hurr icane A v a a n d t ropical s torm Chr is t ine ,one of the met h o d s , used to c om pu te th e wind-f ie ld

character is t ics for a 160 000-km2

area, was developedfo r a program independent of Skylab. The model re-quired inp ut informa t ion rega rding th e speed of move-m e n t of the storm over th e ocean surface, th e centra l

pressure , and the radius of m a x im um w inds . Ea c h cellscanned dur ing th e Skylab pass over th e cyc lone w asassigned an a pp r op r i a t e wi nd direction and speed basedon th is theory .

2 4 2 S K Y L A B E R E P IN V E S TI GA T IO N S S U M M A R Y



ill

O 15 m/sec

D,A,O6.5 m/sec

P,Q 3.0 m/sec

i i iUpwind

i i i i i

-180 -150 -100 -50 I ! 5 0 100 150 180Az imuth ang le , de g

F I G U R E 5-41.—Inf luence o f windspeed an d w i n d d i rec t i o n o n

bac ks c a t t e r in tens i ty f rom airc raf t r a d a r d a t a .

A synop t ic ana lys i s fo r t rop ica l s to rm C hr is t inebased on c onv enti ona l ship board data is show n in f igure5-49, in which the rec tangular area indicates the S193-scanned wid th. Con ventiona l d ata provide very l i t tle in-fo rmat ion on the character is t ics of the w i n d field in at ropical s torm because mar iners avoid these areas.

Although the w i n d s in Ava and Christ ine were deter -mined f rom a theore tica l bo undary - layer model for anin tense moving vor tex , th e theory w as cross checkedagainst data on w i n d s and other param eter s ob ta ined by

ai rcraf t f l ights into both s torms. Fo r Hurr icane Ava , anN O A A C - 1 3 0 ai rcraf t penet r a ted to the eye andmeasured winds near the sea surface at an elevation ofa pp r ox i m a t e l y 150 m and a t other eleva tions wi th in th estorm at the eyewal l . These data, together with centralpressure determined f rom dropsondes into the eye, andglit ter patterns in the per iphery of the s torm were usedto check th e reasonableness of the final model windfield. An ex a m p l e of one check is s h o w n in figure 5-50,in which th e winds measured by the aircraf t are corre-lated with the theoretical winds for the appropr iate sec-tor of the tropical hurr icane (ref . 5-50).

Figure 5-51 (tropical s torm Chr is t ine) provides a

graphic r epresen ta t ion of the meteorologically deter-mined vector w i n d and the measured backscatter valuebefore correc t ion fo r a t tenua t ion and w i t h o u t any con-cern with the variabi l i ty of the backscatter value with

wind d irec t ion . The a r rows that appe ar to l ie in thehor izon ta l p lan e (wi th some p er spec t ive) a r e the values

of the windspeeds and wind direc t ions, as shown by theappropr ia te scales, at each of the cells. Th e spacec raf tpassed over th e b o t t o m m o s t row of cel ls , which corre-spond to the nad i r measurements . For inc idence angles

of 31°, 42°, and 50°, the values of the vert ical ly polar izedand ver t ical ly received backscatter are graphed as ver t i -ca l bars at each cel l . The exact range of var iat ion as afunct ion of windsp eed depe nds on the inc ide nce angle,so these var ia t ions in backsca t te r shou ld be s tud iedalong each l ine at a given incidence angle. For the 31°plot , the backscatter for the low winds in the lower left

is a p p r o x i m a t e l y —18 dB , increases to greater than — 5dB for one of the cells near th e eye, an d then decreaseswith decreasing windspeed to the upper r igh t po in t .Similar r e m a r k s are a p p r o p r i a t e fo r each of the l inesscanned for the other two incidence angles . This f igureis considered highly s ign i f ican t in t h a t it cons t i tu tes th e

most conv inc ing demons t r a t ion of the evident correla-t ion between th e winds near th e surface of the oceanand the measured value of the radar backscatter .

A second method used to determine th e w i n d s in theS193-scanned area was to plot data f rom al l ava ilables h i pp i ng an d coastal reports and p e r f o r m a s t r eaml inei s o t a c h a n a l y s i s of the w i n d f ie ld ( r ef . 5 -49) .

S t r eaml ines are curved l ines everywh ere para l l e l to ther epor ted wind d i r ec t ion , and isotachs are contours of

2CO—

£ 0

I -4

0.35

0. 40.45First-order small-perturbation

theory (a = 0 . 4 )

Ampl i tude of angular

variat ion in capi l lary

wave spectrum

20 40 60 80 100 120

Azimuth angle, deg

140 160 180

F I G U R E 5-48 .—A z i m u t ha l depen den c e of bac ks c a t t e r at 12.9-

m/sec winds peed , 13.9-GHz f r equ en c y , and 60° angle of r adar beam

from the vert ica l a t the surface for various choices o f a 0 for vert ica l -t r a n s m i t / v e r t i c a l - r e c e i v e polar iza t ion ( f rom ref. 5-49).




• • 5 5 5 0

Longitude, d e g W:- .: • (5

Key : - - - A r e a o f S193data

-* -StreamlinesO Ship location

O — W i n d directionO — W indspeed:

Half barb

Ful l barb

O Clear

O O ne-quarter overcast

3 O ne-half overcast

a Three-quarters overcast

• Completely overcast

2.6 m/sec (5 knots)

5. 1 m / s e c (10 knotsl

Three-digit numbers - W ind direction to nearest 10C

m e a s u r e d clockwise from north (0°)

Two-digit numbers - W i n d s p e e d to nearest knot

Five-digit numbers - Sea-level pressure in kP a

(1 k P a = 1 0 m b - l O O O N / m2!

FIGURE 5-49.—Location of S193 pass over tropical storm Christine at 18:00 GMT on September 2, 1973 (af ter ref . 5-49).

equal windspeed . For the subtropical areas of the w o r l d ,t h i s ana lys i s w as per fo rmed fo r numerous Sky lab 2 and3 passes. Th e windspeed and the win d d i r ec t ion at eachof the cel ls scanned were then read f rom th e s t r eaml ine

iso tach a na lys i s .The t h i r d m e t h o d of data ana lys i s was a computer

techn ique ( r ef . 5-49) developed fo r d e t e r m i n i n g w i n d inmidd le - l a t i tude ext r a t rop ica l cyc lones and in other

changing pressure systems. These sys tems p roduce themost im po r tan t day - to -day w i n d f ie lds over th e ocean.In t h i s ana l y t i c t echn ique , th e qual i ty of the var ious re -ports in the area is weighed by source, depending on

w h e t h e r th e repor ts are m a d e by weather sh ips , sh ipsw i t h a n e m o m e t e r s o f k n o w n h e i g h t , s h i p s w i t hanemometer s o f unknown heigh t , o r t r ans ien t sh ipsthat est imate the winds f rom wave appearance. In some




5 0 r

:

a 3 0" g

1 1

,'N\

o o

Model winds

o M easured winds

V 100 150 200

D istance f rom eye, km

50 300 350 10

F I G U R E 5-50.—Comparison of averaged flight-level (150 m ) windspeeds an d model winds in the eastern ( rear) quadrant of Hurr ica ne A va(from ref. 5-49).

areas, no r epor t s were ava i lab le and the w i n d s had to becalcula ted f rom the pressure gradients . For m a n y of thecel ls scanned by the S193 dur i ng Sky lab 2 and 3 , thewi nds were de termined in th i s way ; th i s techn ique wasused for al l the cel ls scanned dur ing Skylab 4. The pro-cedure correc ts for the w ind var ia t ion wit h heigh t abovethe sea surface and refers al l winds to an elevation of19.5 m. It also corrects fo r a tmospher ic ins tab i l i ty ,

whi c h produces an addit ional var iat ion. In effec t , thewi nd w i t h w h i c h th e backscatter measurement w ascompared was the wind tha t would have p roduced thesame wind stress on the sea surface for a n eu t r a l l yst rat i f ied atmosphere.

The scale of the w ind f ields in extra tropic al cyclonesis i l lustrated by an analysis performed by Ross (ref.5-50) as shown in figure 5-52. This cyclone was one ofth e most intense of the past 20 years. The isobar ic pat-tern and the windspeeds repor ted by ships near th e t imeof a Sky lab pass ar e s h o w n . The scales involved can beinferred by compar ison with th e size of the Gulf ofSaint Lawrence, which can be seen in the upper left.

The final resul t of these analyses w as p r o v i d ed in ana p p en d i x to reference 5-49, in w h i c h th e measuredb a c k s c a t t e r v a l u es , t h e p a s s i v e m i c r o w a v e t em -peratures , th e windspeed and wind d i r ec t ion , th e

lat i tude an d long i tude of the cell, and the t ime of the ob-servation are tabulate d. Table 5-I I is taken f romreference 5-49. The S193 azimuth is the direc t iontoward w h i c h th e radar beam is p o i n t i n g . Th e aspectangle is the d i r ec t ion of the win d vec to r r e la t ive to thepo i n t i ng d i r ec t ion of the radar beam. Fo r zero degrees,the beam is poin ting u p w i n d ; plus is c lockwise andmin us is counterc lockw ise.

Correction of the backscatter measurements for theeffects of attenuation using th e pass ive mic rowavemeasurements w as accompl ished by using th e br igh t -ness t e m p e r a t u r e at an i n c i d en c e a n g l e of 50°.D i f f e r en c es b e t w een t h e t em p e r a t u r e s t h a t w e r emeasured and the temperatures that would have beenmeasured (a s determined by the sea-surface tem-perature in the absence of at tenuating effec ts) werecalculated. These dif ferences can be s h o w n to be causedby th e in terven ing c loud d rop le t s and rain between thespacecraf t and the sea surface. This excess m i c r o w a v etempera tu re w as cor re la ted w i th a t tenua t ion based onindependen t measurements of the a tmospher ic tem-

pera tu res and cor respond ing a t tenua t ions made wi th an u m b e r o f g r o u n d - b as e d u p w a r d - l o o k i n g p a s s i v emicrowave receivers . This correlat ion determined thetwo-way a t tenua t ion in decibels for the scatterometer .

O C E A N S A N D A T M O S P H E R E 245



R • Points at which passive

indicate presence

, i

2 5

measurements ^

of heavy rain.

W indspeed scale, m/sec

'«

-15

-2 0

-2 5

-30

(50°

X'420

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"-20

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FIG U RE 5-51.—Comparison of uncorrected radar ba cksca t te r mea su remen ts in t ropica l storm C hr i s t ine and the vector winds at the cellssca nned (from ref . 5-49). Th e symbol o- vv represents vertically polarized and vertically received ba cksca t te r wi t h values expressed in decibels

For Sk ylab 2 and 3, a histogram of the a tten uati on ascalculated at each 50° incidence angle is s h o w n in figure

5-53. Because the backscatter values range over 20 dB ormore as the windspeeds vary from 3 to 25 m/sec , a 0.2-or 0.3-dB correction is quite small and b arely affects thecalculat ion of the windspeed . At tenua t ion could not becom puted for the Skyl ab 4 data because the ant enn a wasdamaged d ur ing the repa i r of the scann ing subsys tem.However , based on Skylab 2 and 3 results, th e inabil i ty

to correct the a t tenua t ion could no t have apprec iab ly

affected the ca lcula t ion of the wind s .For certain cells scanned by the S193, the excess

m i c r o w a v e temperatures were extremely high com-pared to the usual values of the excess m icrow ave tem-pera tu re just described. These "hot" spots are ind ica t iveof large cloud droplets and falling ra in . In this s i tua t ion ,th e measured backscatter cannot be used to ca lcula tewindspeeds because most of i t is coming from theclouds and ra in. Figure 5-54 shows the marked in-creases in passive microw ave tempe rature on one of thelines of cells of constant incidence angle over t ropicals torm C hr is t ine . Even fo r heavy cloud cover in a t ropi -

cal storm, the a ttenuation values are not proh ib i t i ve l ylarge except for the scans in which ve ry sha rp peaks

2 4 6 S K Y L A B E R E P I N V E S TI G AT I ON S S U M M A R Y



55°W 50°W 45°W

Key: • P oints scanned byS193

6 I ncidence angle of Skylab measurements

o Ship locat ion

o Aircraft location

— o W ind d i rect ion

W indspeed:

Hal f barb = 2 .6 m/sec (5 knots)

Ful l barb = 5.1 m/sec 11 0 knots)

Flag - 2 5 . 7 m/sec (50 knots)

I sobars ex press sea- leve l pressure in kPa

(1 kPa = 10 mb = 1 0 0 0 N / m2)

Three-dig i t numbers:

A ir temperature in kelv in (unparenthesized)

Sea temperature in kelv in (parenthesized)

F ive-dig i t numbers:

Upper or only set - Sea cond i t ions

Lower set - Swel l condi t ions

305 02i I '—Sea he i gh t in half meters

— W a v e period in seconds

I— M eteorologica l code

3 3 9 9 61—Swell height in half meters

-Swell period in seconds (0 to 4 = 10 to 14 sec or more)

(5 to 9 = 5 to 9 sec)

— Swe l l direction f rom wh ich waves come in tens of degrees

99 = Confused condit ions

X = M iss ing data

F IGURE 5-52.—Surface w e a t h e r chart of extra tropica l cyclone observed on J a n u a r y 9 , 1974 (from ref. 5-50).




TABLE 5-11.—Merged Meteorological, Oceanographic, Radar Backscatter, and Passive MicrowaveData

for a Portion of the Pass Over Tropical Storm Christine

Scan

.

4

i

•

'

;

1t

: • .

. •

13.4

13.5

14.1

14.2

14.3

14.4

14.5

'• • !

15.2

15.3

1

16.1

II I

II '1 1 . 4

16.5

Incidence

angle.

4 .

..

.9

-

H

II

.9

- >

:.

I6J

.9

49.7

42.1

11

16.7

9

49.7

42.2

31.1

16.7

1.0

49.8

42.1

11 I

|( 1

1.0

49.8

42.2

31.216.8

1.0

Scattering coefficients. dB

-15.22

-11.27

-7.95

•

-14.33

-11.03

-4.25

.

12.04

-13.31

-10.43

-7.06

1.85

12.05

-13.89

-11.37

-6.46

1.82

—

-15.47

-12.21

-7.64

2.05

12.90

-16.74

-14.31

-10.12

-.27

13.12

-17.33

-16.08

-11.171.50

—

tftfa

-19.26

-1336

-864

•

12.25

-18.65

-13.35

-5.73

12.01

-16.05

-12.85

-6.85

1.50

11.85

-19.41

-11.87

-8.63

.88

13.09

-22.13

-14.57

-9.61

15 913.18

-22.43

-18.44

-11.86

0912.97

-23.88

-20.56

-13.151.09

12.80

V H*

-25.80

-21.19

-21.08

-1402

-4.65

-25.84

-21.83

-16.31

-13.48

-5.04

-24.82

-21.77

-18.14

-13.47

-4.58

-26.33

-22.78

-20.40

-14.03

-4.23

-28.89

-24.51

-21.97

-13.91

-3.77

-2933

-27.41

-24.55

-14.19

-4.27

-31.53

-29.87

-26.10-1436

-4.04

W

-25.48

-21.05

-21.38

-14.30

-4.73

-26.11

-21.66

-16.06

-13.25

-5.40

-25.03

-22.06

-1892

-14.13

-5.03

-26.86

-23.11

-20.84

-14.27

-4.70

-28.41

-25.33

-22.41

-14.13

-4.55

-29.16

-27.89

-24.88

-14.77

-4.11

-30.92

-29.92

-25.95-14.79

-4.36

A n t e n n a temperature, K

Kb

175.11

166.30

199.10

15994

134.40

176.41

164.66

165.76

189.58

134.88

184.92

176.41

224.57

160.74

133.11

172.82

207.50

157.47

161.75

132.71

171.16

167.44

146.38

138.55

129.21

170.87

160.24

144.94

174.26

127.87

169.62

15 8.24

145.10132.67

127.85

tfb

118.20

127.40

198.13

168.10

131.29

118.98

124.29

146.69

165.69

135.35

127.92

128.35

212.49

164.19

133.60

111.84

145.53

132.22

144.31

132.66

109.68

119.43

122.77

130.60

129.71

107.82

115.85

122.38

163.53

129.39

105.54

111.85

120.45125.86

128.31

Aspect

angle, deg

86.4

134.1

-189.2

-172.1

130.0

107.3

128.0

152.7

163.6

119.6

120.1

131.9

145.7

154.3

112.2

126.9

135.8

144.5

150.1

102.4

132.8

138.5

145.2

148.9

102.1

136.5

142.4

146.9

150.2

107.2

140.3

144.2

148.9150.5

130.1

Windspeed.

mfsec

.

•

•

19.0

22.1

•

14.4

•'

•

.

"

14.4

4.9

i .

13.9

12.9

12.4

12.9

12.4

12.4

! •

10.8

10.8

IOJ10.8

10.3

9.3

9.3

9.3• |93

Sea em-

perature, K

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301 16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301.16

301 .16

301.16

301.16301.16

301.16

GMT.

hr:mm:sec

17:56:32.5

17:56:36.0

17:56:39.2

17:56:42.0

17:56:44.2

17:56:47.7

17:56:51.2

17:56:54.5

17:56:57.2

17:56:59.4

17:57:03.0

17:57:06.5

17:57:09.8

17:57:12.5

17:57:14.7

17:57:18.2

17:57:21.7

17:57:25.0

17:57:27.7

17:57:29.9

17:57:33.5

17:57:37.0

17:57:40.2

17:57:43.0

17:57:45.2

17:57:48.7

17:57:52.2

17:57:55.5

17:57:58.2

17:58:00.4

17:58:04.0

17:58:07.5

17:58:10.717:58:13.5

17:58:15.7

Celt coordinates, deg

Lai .N

16.55

16.14

15.61

15.03

14.45

17.30

16.88

16.35

15.77

15.19

18.05

17.63

17 .10

16.52

15.93

18.80

18.37

17.84

17.26

16.67

19.54

19.12

18.59

17.99

17.40

20.30

19.85

19.33

18.72

18.14

21.04

20.60

20.0519.45

18.87

Long. W

59.28

58.44

57 .52

56.58

55.70

58.68

57.83

56.91

55.98

55.09

58.07

57.22

56.30

55.36

54.48

57.46

56.61

55.68

54.74

53.85

56.84

55.99

55.06

54.12

53.23

56.22

55.36

54.43

53.49

52.59

55.60

54.74

53.8052.85

51.96

SI 93

azimulh

angle, deg

312.6

312.9

313.2

314.1

•

312.7

313.0

313.3

314.4

1.4

312.9

313.1

313.3

314.7

8

313.1

313.2

313.5

3149

6.6

313.2

313.5

313.8

315.1

4.9

313.5

313.6

3 1 4 1

314.8

359.8

313.7

313.8

314.1315.5

7.9

aVV, vertical transmit, vertical receive; HH, horizontal transmit , horizontal receive; VH. vertical transmit, horizontal receive; HV. horizontal transmit, ver t i ca l receive.

bV, v e r t i c a l transmit; H. h o r i z o n t a l transmit.

have occurred. The f ive small R 's in figure 5-51showinstances in w h i c h the winds could not be calcula tedfrom the backscatter in t ropical s torm Chr is t inebecause of this effect.

M a n y different m e t h o d s were used to s tudy th e rela-t ionsh ip between th e measured backscatter values andthe windspeed , a l l based on the a ssumpt ion tha t themeteorological ly de te r m ine d w ind direc t ion w as cor-

rect. All the techniques were var iat ions of multiple-regression schemes . A func t iona l form for the depen-

dence of windspeed on backscatter was used. Th evar ious u n k n o w n cons tan t s in tha t funct ional form

were de te rmined by m i n i m i z i ng th e sums of the squaresof the differences between the windspeeds tha t wouldbe predic ted from th e r adar measurements by mea n s ofth is analyt ical form and the meteorological wi nds . The




2 0 r

15 -

10 -

•

-

-

1

I05

•

13

12

11'

-—

Geometric mean = 0 . 2 d B

100010

=1.023

100020 -1 .047

ID0'03 0 - 1 . 072

ID0

'04 0

-1.0%ID

0'050

-1.122

12 ID0'06 0

-1.148

8

f

4

n » iI"

2 J 2

l i n n i f, n n r n . r l ,

.20 .25 .30 .35 .40 .45 .50 .55 .60 .6Two-way attenuation, dB

FIGURE 5-53.—Histogram of 118t w o- w ay attenuation values at 50°

incidence angles for S k y l a b 2 and 3 (ref. 5-49).

250 r

1 200

•• = 1 0 0

Backscatter

o o o o o °

D D D D DC

1 1 1 1 1 f 1

D

M i s s i n g d a t a ^

D 0 D D Q \,

i i i i i i i i i3 4 5 6 7 9 10 11 12 13 14 15 16 17 18 19 20Scan n u m b e r

F I G U R E 5-54.—Graph of the values of ve r t i c a l ly (circles) and

h or i zon t a l ly (squares) polarized passive m i c r o w a v e temperatures at

31° incidence angle for t rop i ca l storm Christine (from ref. 5-49).

personnel , are the most ac curate . Transient ship s pro-vide repor ts of var iab le quali ty depending on w h e t h e ror not they have anemomete rs and whe ther or not theheight of the ane mome t e r has been reported. If the shiphas no anemom ete r , the windspeed and w ind d i rec t ionare estimated. M oreover , the reports are from sh ips that

are scattered unevenly over th e oceans, being concen-tra ted a long the ship pin g lanes and widely spaced other-wise.

The analysis of the ship reports involves the bound-a ry - l ayer theory of Cardone (ref. 5-51), in wh ich re la-

t ionsh ips among th e pressure gradients, the a ir /sea- tem-perature differences, and the winds are used to form a

results of the analysis of the paired sets of meteorologi-cal winds and rada r winds were then graphed.

Th e graph fo r tropical storm Christine and Hur-

r icane Ava , for all three nadir angles and for cross-polar ized radar backscatter , is show n in figure 5-55. Thedistance of the plo tted poin ts from the true value can becaused either by errors in the radar part of the theory orby errors in the determination of the meteorologicalwind. I t was the re fore ve ry impor ta nt to obta in an inde -pen den t estimate of the errors in the w ind, and this esti-mate was accomplished only for the objective syno ptic-scale analyses. I t was f ound tha t th e meteorologicallyde te rmined sur face - t ru th wind h as substantia l error .

Th e winds over th e ocean are de te rmined f romanalysis of ship reports of windspeed , wi nd direc t ion ,surface a tmosph er ic pressure, a ir tempera ture , and sea

tempera ture . Some repor ts are made from weatherships th at remain in one place to make scheduled obser-vations l ike those of a weather station on land. Ingeneral , these reports, made by tra ined meteorological

2 5

20

•I 15

§10

O Sing le point

3 Two coincident points

• Three coincident points

10 15 20 25R adar-derived windspeed, m/sec

•

F I G U R E 5-55.—Graph of accuracy of w i nd determination from

backscatter v a l u e s (from ref. 5-49).




con t inuous field of the vector winds at a fixed heigh tabove the sea surface. The accuracy of such an analysisin determin ing the ac tua l winds depends on the qu a l i ty

and spacing of the available ship repor ts .

To determine th e accuracy of the exist ing conven-t ional m e t h o d s fo r d e t e r m i n i n g th e winds near th e sur-

face of the ocean , th e da ta w ere ana lyzed separa te ly fo rth e entire per iod by mea n s of a "wi thheld weather sh i p"t echn ique . Firs t , th e w i n d f ie lds were analyzed as j us tdiscussed with th e weather sh ip da ta incorpora ted .T h en th e weather ship data were removed and theana lys i s w as repeated. Th e differences between the twor esu l tan t winds a t po in ts near th e weather ship werequite large and depended on the qual i t y of the data thatreplaced the weather ship data for the area in question.Errors in the sp ecif icat ion of the w inds were larger tha nthose fo r a weather sh ip r epor t w hen the w inds were re -por ted by an ord inary t r ans ien t sh ip and s t i l l larger if

th e w i n d had to be determined f rom th e isobar ic pattern

and th e ava i lab le boun dary - laye r theory .It w as possible to par t i t i on th e total mean-square

d i f f e r e n c e b e t w e e n t h e r a d a r w i n d s a n d t h emeteorological winds into a contr ibution f rom the er -rors in the meteorological ly specif ied winds and a con-t r ibu t ion from the radar specif ied winds. The regressionequations yielded a windspeed predic ted f rom th e r adarbackscatter measurement, given th e w i n d d i r ec t io n , sot h a t for the three highest n ad ir angles , pairs of values ofth e r a d a r w i n d s p e e d U r a n d t h e m et eo r o l o g i c a l

windspeed U m were th e result. The total variance ofthese quan t i t ies for N samples given by

Tota l var iance

N

= -£N *-"

(U.\ ri

- U (5-3)

where al l samples f rom 1 to m o r e than 800 were ad -dressed, is a mea s u re of the var iat ion between tw odi f fe rent w a y s of determin ing th e wind . Bo th t/,and U m

contain er ro rs and differ f rom th e t rue b u t u n k n o w nvalue of the windspeed U T , w i t h the error dif ferencegiven by

U -

m

Because th e total var iance is k n o w n , it is possible toc o m p u t e th e error var iance of the meteorological winds

and the error var iance of the radar winds that consti tuteth e total var iance.

The term for the meteorological var iances was deter -m i n ed by the withheld weather sh ip techn ique . Theterm for the radar var iance w as d e t e r m i n ed by c o m p a r -in g dif ferent po lar iza t ions . Th e results are prov ided in

table 5-III, as strat if ied according to the qu a l i ty of themeteorological sur f ace- t ru th and windspeed ranges.M o r e t h a n 800 separate cel ls were scanned by the S193fo r these s tudies dur ing 14 Z-axis-to-local-verticalpasses. This amount of data fa r exceeds that of all pre-vious aircraft programs. The total variance for a largesample should equal the sum of the two par ts . I t doesnot because of sampling v ar iab i l i ty ; however , the sumsnea r ly balance. Fo r some categories, the two t e rms onth e right add up to less than th e term on the left. Thedifference i s shown under the unex p la ine d var iance .Th e italicized values represent those categor ies wherethe two terms on the right exceed th e term on the left.

Al though the er rors in the meteorological wind weredetermined f rom a dif ferent data base, the resul ts

near ly balance category by category . Most of thedifference between the r adar w i n d and the meteorologi-cal win d is due to "errors" in the meteorological wind.

Cardone et al. (ref. 5-49) concluded that the

windspeeds computed f rom th e backscatter measure-m e n t s at each cell, after correct ion fo r a t t en u a t i o n an dunder the assumption that the wind direc t ion was cor -rect , were at least as accurate as those that would havebeen recorded by a weather ship located at (or near)each cell. It was also stated that this conclusion was aconserva t ive in terp re ta t ion of the results of the s t u d y .

The s tandard dev ia t ion of the errors of the radar -measured wind may well be less than half that of the er -rors in the winds presently repor ted by weather ships .

The radar backscatter theor ies developed in this pro-gram and the AAFE data were used as a guide in for-mul a t ing th e regression equations that were used. Theseregression equations with unknown constants , deter -mined f rom Skylab backscatter measureme nts and thewinds, need not necessarily have agreed wi th either thetheory or the AAFE da ta . However , they d id . Th eresults of one regression method in which radar back-scatter is plot ted against azimuth angle for threedifferent windspeeds ar e shown in figure 5-56. Th e

agreement wi th figure 5-47 as to shap e and re lat ive sepa-ratio n is very good. The disag reem ent as to absolute

level can be at tr ibuted to SI93 recal ibrat ion problemsdur ing Skylab 4.




TABLE 5-7/7.—Component Variance Analysisfor the Three Highest Nadir Angles

[From ref. 5-49]

(a ) Skylab 2 and 3 data

Windspeed

range,

knots

efl to 10ell to 20

e21 to 30

0 to 10

11 to 20

21 to 30

0 to 10

11 to 20

21 to 30

0 to 10

11 to 20

21 to 30

0 to 10

11 to 20

21 to 30

0 to 10

11 to 20

21 to 30

Type

A

A

A

B

B

B

C

c

cI )DD

B CD

BC D

B CD

SY N

S YN

S Y N

Variance, (knots):

y y b

11.2

M

—

35.5

27.4

99

t ,5

12.3

15.3

1 4 . "1

—

15.4

18.7

75.1

1 1

15.7

55.8

Total

HHb

9.9

104.0

52.1

28.5

57.3

8. 8

1 3 . 2

21.3

1.3p . o66.1

22.6

21.1

44.6

8.88

13.5

56.2

HWH*

10.4

78.7

51.0

25.3

47.5

5.610.2

13.3

t , 2

18.1

—

27.5

18.6

36.1

10.7

14.0

35.4

Meteor-

ological

5.7

12.5

19.1

12.9

25.8

39.5

12 .4

25.8

39.3

1 2 . 4

25.8

39.5

12.9

25.8

39.5

27.9

35.1

55.8

Unexplained variance.

Radar (c)

vv

\ 4

1.9

1.9

1.91.91 4

1 4

1 .4

1 4

1 .4

1 4

1.9

1.9

1.91.9

1.9

1.9

1.9

HH

0.9

.9

.9

.9

.9

.9

.4

4

.9

.9

.4

.9

.9

.9

.9

.9

.9

.9

HVIVH

\ I

1 2

1 2

1.2

1.2

1.2

1.2

1.2

1 .2

1 2

1 .2

1.2

1.2

1.2

1.2

1.2

1.2

1 .2

\ >

3.6

69.6

—

20.7

J

57.6

gj

isj

25.S

13.0—

.6

9.033.7

18.8

21.3

1.9

HH

3.5

84.0

38.3

1.8

16.9

5.013.5

19. J

U' i . l

25.7

8.85.6

4.2

19.9

22.5

.5

HVIVH

3.3

58.4

36.9

1. 7

(• 8

8.5

16.8

27.2

7 .9g , ' i

—

13.4

8.4

4.6

18.4

22.3

21.6

Unexplained standard No. of cells

deviation, knots

(d )

vv

1.9

8.3

—

4.5

.5

7.6

2.93.9

fj

3.t

—

.8

3.05.8

4. 3

4.6

1.4

HH

1.9

9. 2

6.2

1.34.1

2 . 2

3.7

4.4

2.33.05.1

3.0

2.4

2.0

4.5

4. 7

.7

HVIVH

1.8

7.6

6.1

1.3

2.6

2.94 1

'•-

2.SI."

—

3.7

2.9

2.1

4.3

4. 7

4.6

V V

16

3

—

4

49

5

4

M

2

2 8

—

13

128

7

24

135

6

scannea

HH

17

3

8

48

2

1 !

M

2

6

2 31

25

107

5

39130

6

HVIVH

16

3

848

2

4

37

1

2

2 ( ,

—

19

111

3

34

127

3

Totas 332 332 316

aA-type data are for weather ships an d aircraft underflights . The B-, C-, and D-type data are for ship repor ts of decreasing qual i ty ; SY N represents those cells for w h i c h the windspeed had to

be determined from the i sobaric pa t tern and the boundary - laye r theory. Th e meteorological variance is lowest for t y p e A; the same for B, C, and D; and highest fo r S Y N .

byv , ver t ical t ransmit , vertical receive; HH , horizon tal t ransmit , hor izon tal receive; HV , horizon tal t ransmit , vertical receive; V H, vertical transmit, horizontal receive.

I t a l i ci zed numbers represen t th e amo u n t s by which the sum of the meteorological-error variance and the radar-erro r var iance exceeds th e total variance.

^ Ital ic ized n u mber s are the square roots of the corresponding values in the three corresponding preceding co lumns.

ZQ to 10 knots — 0 to 5.1 m/sec; 11 to 20 knots — 5.6 to 10.3 m/sec; 21 to 30 knots — 10.8 to 15.4 m/sec.fExclud ing type BCD.

C O N C L U S I O N S

Oceans

A ll Sky lab ER EP ins t ruments were found to be

va luab le in s tudy ing the oceans. Sea-surface tem-peratures were measured f rom orbit by the InfraredSpectrometer . Atmospher ic effec ts on the measure-ments were corrected to an accuracy of ±1 K by

ana lys i s of data in two selected wavelengths sensed bythe ins t rume nt . The M ul t i spec t r a l Scanner acqu i r eddata that were used to por t r ay thermal pa t te rns of oceancur ren ts and upw el l ings and to de termine dep th o f c lear

w a t e r t o 1 8 m . T h e M i c r o w a v e R a d i o m e t e r / -Scatterometer obtained surface roughness data that

verified theor ies and techniques that wil l be used in thefuture to observe se a ice, se a state, and winds over th eoceans on a global scale not possible by any othermethod. Investigators used Microwave Alt imeter data




T A B L E 5-IIL— Concluded

(b ) Skylab 4 data

Windspeed

range,

knots

ell to 20

e21 to 30

<H ) to 10

1 1 to 20

21 to 30

>30

11 to 20

21 to 30

>30

Oto 10

1 1 to 20

21 to 30

>30

O t o 1 0

11 to 20

21 to 30

>30

O t o 1 0

11 to 20

21 to 30

>30

TypeiHi

X

\

I )

B

li

B

C<

<

1 )

1 )

DD

BC DB C D

BC DBC D

S Y NSY N

S Y N

SY N

Variance, (knots ):

W*

32.4

,4 4

2.31

21.7

37.6

65.0

It 9

20.1

88.7

327.6

52.4

64.3

2.65

24.4

43.6

67

43.2

32.1

64.6

116.6

Total

HH *

0 1

. 6

23.4

50.7

81.0

10.976.4

67.9

109.4

37.3

109.4

41.7

57.8

29.7

87.6

49.8

48.7

28.5

80.1

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67.9

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Totalsf 47 9 4 ' < 4 47 0

3A- l yp e data are fo r weathe r ships and ai rc raf t underf l igh ts . The B - . C- , and D -type data are fo r ship repor ts of decreasing qua l i ty ; SYN represen ts those cells for which the windspeed had to

be de te rmined f rom th e isobaric pattern and the boundary - laye r theory . Th e meteoro log ical varianc e is lowest fo r t y p e A; the same for B, C. and D; and highest fo r S Y N .

^VV, ve rt ical t ransmit , ve rt ical rece ive ; HH , horizontal transmit, horizontal receive; HV , horizon tal t ra nsmit , ve rt ical receive ; VH , vertical t ransmit , horizon tal receive.

Italicized numbers represen t th e am o u n t s by w h ic h the sum of the meteorological-error variance and the radar-e rro r variance exceeds th e to tal variance .

^ Ital ic ized numbers are the square roots of the corresponding values in the three corresponding preceding co lumns .eO to 10 knots - 0 to 5.1m/sec; 11 to 20knots - 5.6 to 10.3 m/sec; 21 to 30 knots - 10.8 to 15.4 m/sec

E xc l u d i n g type B C D

to demonstrate that th e con tour of the ocean surfacecan be measured to an accuracy of ± 1 m or better . In -forma tion was obtained in passive mic row ave data that

could be used to determine surface roughness and pre-c ip i t a t ion in the atmosph ere.

The L-Band R adiom eter resul ts indic ate that sea-sur-face roughness measurements as related to windspeed

may be obtained at L-band f requencies when other f re-quencies are not usable because of precipitat ion inter -ference. The L-band data were not suitable fo r measur-

in g sea-surface sa l ini t ies or temperatures on the openocean.

The photographs f rom the Mul t i spec t r a l Pho to -graphic and Earth Terrain Cameras were used to dis-

2 5 2 S K Y L A B E R E P IN V E S TI G A TI O N S S U M M A R Y



:

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.

.

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A z i m u t h a n g l e , d e g. -

F I G U R E 5-56.—Regression curves ve ri fy ing a i rcraft data presentedin figure 5-47 (from ref. 5-49).

cern and record v i s ib l e ph eno me na such as water color ,t u r b i d i t y , depth , cur rent and wave pa t t e rns , shoa l ex -

t en t an d l oca t ion , c h l o r o p h y l l c on t e n t , and ice types andpa t t e r n s .

Th e availabil i ty of da ta acqui red s imul taneous lyfrom two o r m o r e ins t ruments provided bases fo r con-c lus ions tha t would not be suppor tab le i f only one in -s t rument had been used . S tudy of l iv in g m a r i n eresources is an example . Cer ta in t empera tures arefavorable to gr owt h o f p l a n t a nd a n i m a l l ife b u t l oca t ingareas of a pp r op r i a t e t e m pe r a t u r e s y i e ld s i nc onc l u s i veresults in any search for l iv ing organisms. If , in ad di t io nto data on sui t ab le t empera ture , wa te r -co lor informa-

tion is avai la ble from a scanner or a camera , th e searcharea can be reduced. If s upp l e m e n t a r y i n f o r m a t i on on

currents , measured by scanners , cameras , or a l t imete rs ,i s provided , th e resul ts can be f u r t he r i m pr ove d .

Subt le grada t ions of con tour , t ex ture , co lor , and tem-p e r a t u r e , w h i c h a r e i m p o s s i b l e t o o b t a i n w h e nmeasured at or near th e surface, can be observed fromspace and in te r re l a t ionships can be evaluated. Severalinves t iga tors used Skylab EREP da ta conta in ing suchinformat ion to s tudy ocean cur rent s , which invo lve

mo s t , if not all , of these factors. The super ior i ty of theda ta acqui red f rom orb i t was demons t ra ted for ma ny

appl i ca t ions .

A tm osphe r e

The Sky lab E RE P inves t iga t ions resu l ted in signifi-

cant advances in the unde r s t a nd i ng of the phys ics of the

a t m o s p h e r e a n d t h e i n t e r a c t i o n b e t w e e n t he a t -m os phe r e and the land an d ocean sur faces . W i tho utdoubt , t he mos t s ignif icant deve lop men t in s a te l li t emeteorology re sul t in g f rom Sky lab was the use of themicrowave spec t rum to measure th e surface wind over

th e ocean. Th e poss ib i l i t i e s fo r ob t a i n i ng m a r k e d l y im -

proved w ind info rm at io n ac ros s a reas of the open oceanw i l l be of majo r usefulness not on ly to we ather forecas t-in g but a l so to sh ip pin g .

A n a l y t i c t echniques w ere deve loped for and new in-forma t ion was ga ined on the loca t ion and conce nt ra t ion

o f pa r t i c l e l ayers in the s t ra tosphere . Skylab provided ,fo r the f irs t t ime , measurements fo r s t u d y i n g th espectra l t ransfer of visible and t he rma l rad ia t ionthrough aerosol layers in the t r opos phe r e and pe r m i t t e dreal is t ic evaluat ion of methods for correct ing the effectsof a t m os phe r i c a t t e nua t i on fo r remote sensing of theEarth ' s surface.

The S k y l a b E R E P pho t og r a phs p r ov i de d i n f o r m a -

t ion fo r s t u d y i n g th e phe nom e non of cloud streets—th e or ienta t ion and spac ing of cloud b a n d s as a func t ionof th e ho r i zon t a l w i nd f ield . Ne w k nowl e dge w as gainedand mathemat i ca l a lgor i thms were deve loped to de-scribe th e r e l a t i ons h i p of phys ica l c loud pa ramete rs tot he ve r t i ca l wind f i e ld .

Th e Skylab exp er im ents deve loped t echniques fo rd i s c r i m i n a t i n g between cloud ice crys ta ls , c loud waterdrople t s , and sur face snow. These e x p e r i m e n t s wi l l lead

to the exper imenta l des igns fo r programs du r i ng th eSpace Shut t l e f l ights to solve th e prob lem of dis-c r i m i n a t i n g supercooled water drop lets , mix tures of icecrys ta l s and wa te r drople t s , and the l ike .

Several ER E P inv es t iga t ions were conduc ted toascerta in the usefulness of mic row ave radiometers forso i l mois ture de te rmina t ion . A l though th e state of thea r t i n l onge r wa ve l e ng t h m i c r owa ve r a d i om e t r y pe r m i t -te d only synopt ic -s ca l e measurements wi th an ins tan-taneous field of v iew of 100 km and m or e in d iamete r , i twas learned th at the L- band is wel l sui ted for m onito r-in g surface soi l mois ture under a wide va r ie ty ofwea ther , vege ta t ion , and t e r ra in con di t ions .

Oceans and Atmosphere

T h e ER EP exper imen ts demons t ra ted th a t th eoceans and the a tmosphere over th e oceans m us t b es tudied j o i n t l y a nd s i m u l t a ne ous l y . Th e m e a s u r e m e n tof th e winds over th e ocean de pe nds on the propert ies




of the waves generated by the w i n d s and on ocean tem-pera tu re measurements . Measurements by mea n s ofeither infrared o r pass ive mic rowave ins t ruments haveto be corrected for the effects of the a t m o s p h e r e .

On the bas i s o f Sky lab -der ived knowledge , improv edversions of the S191, S192, S193, an d S194 instruments

wil l con t inue to be b u i l t for use on u n m a n n e dspacecraft . Mul t i spec t r a l scanner s a r e a l r eady onboardth e Landsa t ; an improved a l t imeter is onboard GEOS-3,and an even more accurate model wil l be used onSeasat-A. Passive microwave sensors will be inc ludedo n N i m b u s an d Seasat-A; dual infrared bands, o n Tiros.Radar backsca t te r will be measured on Seasat-A. Thecombined s tudy of the oceans and a t m o s p h e r e wil l b eposs ib le wi th these new ins t rum ents to an ex ten t neverbefore possible.

The Sky lab exp er imen t a lso demonst r ated the va lueof hav ing the spacec raft manned by t r a ined c r ewm en.T h e crew's abil i ty to acqu i r e and track a ta rget wi t h th e

S191 ins t rument p roved usefu l in acqu i r ing spec t ra l in -forma t ion a t a var ie ty of viewing ang les . Handheld -c a m er a p h o t o g r a p h y s u p p l em en t ed t h e E R E P d a t a f o rthe f loa t ing ice exper iment . The exper ience ga ined inthe combined uses of t r a ined c r ewmen w i t h c o m p l e x ,new, unproven ins t ruments can be the basis fo r opera-t ional plans fo r using th e Space Shutt le in fu r the r sc ien -tific s tudy of the E a r t h .

R E F E R E N C E S

5-1. V o n b u n , F. O. ; M cGoogan , J .; M a r s h , J . ; and L e rch , F. J . :

Sea S ur face D e t e rm i na t i on F rom S p ace : Th e GSFC Geoid .N A S A T M X-70959, 1975.

5 - 2. M o urad , A . G . ; Gop a la p i l l a i , S . ; Ku h ne r , M . ; and Fubara , D .

M .: The A p p l i c a t i o n of S k y l a b A l t i m e t r y to M a r i n e GeoidDetermination. N A S A C R -14 4 372 ,1975 .

5-3. McGoogan, J . T. ; Leitao, C. D. ; and Wells , W . T .: S u m m a r y

of S ky lab S - 19 3 A l t i m e t e r A l t i t ud e Re s u l ts . N AS A T M

X-69355, 1975.

5-4. G r e e n w o o d , J . A r t h u r ; N a t h a n , A l a n ; e t a l .: R a d a r A l t i m e -

tr y F rom a S p ace c ra f t and Its Pot e n t i a l Ap p l i c a t i ons toGeodesy. Remote Sensing Envi ron. , vol . 1, no. 1, M ar. 1969 ,

pp. 59-70.

5-5. G r e e n w o o d , J . A r t h u r ; Na t h an , A lan ; e t a l . : Oce an ograp h i c

Applicat ions of Radar Al t i m e t ry From a Spacecraft. Remote

Sensing Envi ron. , vol . 1, no. 1, M ar. 1969, pp. 71-80.

5 -6 . An d i ng , D av i d C . ; and W alke r , Joh n P . : Us e o f S ky lab

E RE P D at a i n a S e a - S ur f ace T e m p e ra t u re E x p e r i m e nt

NASA CR-144479 , 1975.

5-7 . Holl inger , James P . ; and L e rn e r , Robe r t M . : An a lys i s o f

M i c r o w a v e R a d i o m e t r i c M e a s u r e m e n t s F r o m S k y l a b

NA S A CR- 1 4 7 4 4 2 , 1 9 75 .

5 - 8 . T rum bul l , J am e s V . A . : T h e U t i l i t y of S ky l a b Photoin

terpreted Earth Resources Data in Studies of M ar i ne

G eo lo g y and Coastal Processes in Puerto Rico and the Vi rgin

Is lands . NASA CR-147437 , 1975.

5-9 . Polcyn, Fabian C. ; and Ly zeng a, Da vid R. : S ky l a b R e m o t e

B a t h y m e t r y E x p e r i m e nt . NA S A CR- 1 4 44 8 2, 1 97 6 .

5 - 1 0 . Cam p be l l , W . J .; Ram s e i e r , R. O . ; W e a v e r, R. J.; and W e e k s

W . F. : Skylab F loa t i ng I ce E x p e r i m e nt . NAS A CR- 1 4 7 4 4 6

1975.

5-11. Pir ie , D ouglas M . ; and S t e l l er , D a v i d D . : Ca l i fo r n i a Coas t a

Processes Study. NASA C R -14 4 4 89 , 1975.

5-12. N i c h o l s , M a y n a r d M .: S ou t h e rn Ch e s ap e ake B ay W at e r Co l-

o r and Ci r cu la t i on Ana lys i s . Wat e r Co lo r and Ci r cu la t i on

S out h e rn C h e s ap e ake B ay , Par t I . NA S A C R- 1 4 1 40 4 , 19 7 5.

5-13. G o r d o n , H ayd e n H . ; and N i ch o l s , M ayn ard M . : S ky lab M S S

v s P h o t o g r a p h y fo r E s t uar i n e W at e r Co lo r C las s i f i c a ti on

W at e r Co lo r and Ci r cu la t i on S ou t h e rn Ch e s ap e ake B ay , Par

II. NASA CR-141404, 1975.

5-14. M ars ha ll , Harold G. ; and Bow ker , Da vid E.: The Use of

Skylab in the Study of Product ivi ty Along th e Eastern Shelf

W at e rs of the Uni t e d States. NASA CR-144908 , 1976 .

5-15. K o r b , C . L aure nce ; an d Pot te r , John F. : Ocean Propert ies .

N A S A T M X - 7 2 9 6 1 , 1 9 7 6 .

5 - 16 . S ze k i e ld a , Kar l - H e i nz : D yn am i cs o f Plank t on Pop u la t i ons in

Upwe l l in g Areas . NASA CR-144480, 1975.

5 - 17 . W at anabe , Kan t a ro ; Ku rod a , Ry uya ; H at a , Ka t s u m i ; and

A k a g a w a , M a s a o m i : S t u d y of Sea Ice in the Sea of O k h o t s k

a n d I t s I n f l u e n c e o n t h e O y a s h i o C u r r e n t . N A S A

CR-144472, 1975.

5-18 . Savastano , K. J . : A p p l i ca t i on of Remote Sensing for F ishery

Re s ources As s e s s m e nt and M oni t o r i ng . NA S A CR- 1 4 7 5 0 7

1975.

5-19 . Break er , Law rence C. : A Quali t at ive Look at Sea Surfac e

T e m p e r a t u r e off the W e s t Coast of the Un i t e d S t a te s as Seen

by U H R R I m a g e r y From t h e N O A A - 3 S a te l li te . N O A A ,

Redwood Ci ty , Cali f . , 1974.

5-20. B akun , A . : D a i ly and W e e k ly Up w e l l i ng Ind i ce s , We s t Coast

of Nor t h Amer ic a , 1967-73. N O A A Tech. Re p . NM F S

S S RF- 6 93 . N O A A Na t i ona l M ar i n e F i s h e r i e s S e rv ice , 1 9 75 .

2 5 4 S K Y L A B E R E P IN V E S T IG A T I O N S S U M M A R Y



5-21. B ak un , A . ; and Ne ls on , C . S . : C l i m at o logy of Up w e l l i n g Re -

lated Processes off Baja Ca l i fo r n i a . Paper p resented at the

S ym p os i um on F i s h e r i e s S c ie nce a t th e A ut onom ous U ni v .

of Baja Calif. , Ensen ada , Baja C alif. , Feb. 16-22, 1975.

5-22. Kle m as , V y t au t as ; B ar t l e t t , D av i d S . ; e t a l . : S k y la b / E R E P

A p p l i c a t i o n to Ecological , Geological , and Oc eanog raphic In -

ve s t iga t i ons o f D e law are B ay . NAS A C R- 1 4 4 9 1 0 , 1 9 7 6.

5 -23 . M a r u y a s u , T a k a k a z u ; O c h i a i , H i r o a k i ; a n d N a k a n o ,

T akam as a : In ve s t i ga t i on o f E n v i r o n m e n t a l C h a n g e Pat t e rns

in Jap an . NAS A CR- 1 4 4 5 6 9 , 1 9 7 5 .

5-24. Piech, K e n n e t h R .; Schot t , John R.; and S t e w ar t , Ke n t on

M .: S 1 90 In t e rp re t a t i on T e ch n i q ue s D e ve lop m e nt and Ap -

p l i c a t io n s t o Ne w Y ork S t a te W at e r Resources . N A S A

CR-144499, 1975.

5-25. Y os t , E d w ard F.: In S i t u S p e c t ro rad i om e t r i c Ca l i b ra t i on of

E R E P Im age ry and E s t ua r i ne and Coas t a l Oce anograp h y of

Block I s l and S ound an d A d j a c e n t N ew Y ork Coas t a l Wat e r s .

NAS A CR- 1 4 7 4 6 9 , 1 9 7 5 .

5-26 . Maul, George A .; G o r d o n , H ow ard R. ; e t a l . : An E x p e r i -m e nt t o E va l ua t e S ky l ab E ar t h Reso u rces Sensors for Detec-

t ion of the Gulf St ream. NASA CR-147454, 1976 .

5-27. Ch ang , D av i d T . ; and I s aac s, Rona ld G . : E x p e r i m e nt a l

E v a l u a t i o n o f A t m o s p h e r i c E f f e c t s o n R a d i o m e t r i c

M e a s u r e m e n t s U s i n g t h e E R E P o f S k y l a b . N A S A

CR-144500, 1975.

5-28. Pi t t s , David E .; S a s a ki , Y o s h i k a z u ; an d Lee, Jean T. , com -

pilers : S e ve re S t o rm E nvi ronm e nt s : A S k y l ab E R E P F i na l

Re p or t . NAS A TM X-58184, 1976.

5 - 29 . Cu r ran , Robe r t J .; S a lom ons on , V i nc e n t V . ; and S h e nk ,

W i l l i a m : T h e A p p l i c a t i on o f Satel l i te D at a i n th e D e t e rm i na -

t i on o f Oce an T e m p e ra t u re s and Cloud Ch arac t e r i s t i c s and

Statist ics. NASA CR-147539, 1976.

5 - 30 . Kuh n , P. M.; M a r l a t t , W . E. ; and Wh i t e h e ad , V. S. : The

S ky lab Con ce n t r a t e d A t m os p h e r i c Rad i a t i on P ro je c t. NA S A

CR- 1 4 4 4 8 1 , 1 9 7 5 .

5-31. T h o m s o n , F. J . : M ac hin e Process ing of S-192 and Sup po rt ing

Air c r a f t Data: S tud ies o f At m os p h e r i c E f f e c t s , A g r i c u l t u r a l

Clas s i f i c a t i ons , a n d L a n d R e s o u r c e M a p p i n g . N A S A

CR-144503, 1975.

5 - 32 . T i nge y , D av i d L . ; and Po t te r , Joh n : Q ua n t i t a t i ve D e t e rm i na -

t i on o f S t r a t os p h e r i c Ae ros o l Ch ara c t e r i s t i c s . N AS A

CR-147444, 1975.

5-33. Turn er , Robert E . : Invest ig at ion of Earth ' s Albedo Using

S ky l a b Data. NASA CR-147445, 1976 .

5-34. Ray le igh , J . W . S t r u t t : On the Ligh t F rom the Sky; I t s

Polar izat ion an d Colour . Phi l . Mag. , vol . 41 , 1871, pp .107-120 and 274-279.

5-35 . Mie , G .: C o n t r i b u t i o n s to the Opt ics of Dens e M e d i a of

Special Colloidal Meta l Solut ions . A nn. Phy sik , vol . 25 , 1908 ,

pp . 377445.

5-36. Van de Hu ls t , H. C. : Scat te r ing in a Plan e tary Atm osp her e .

Astrophys. J. , vol. 107, no. 2, 1948, pp. 220-246.

5 - 37. M ar la t t , W . E . : T h e Effect of We a t h e r M od i f ic a t i ons onP h ys i ca l Processes. T h e M i c roc l i m at e i n Ground L e ve l

C l ima to lo g y , R. H. S h aw , e d ., A AA S (Wa s h i ng t on , D.C . ) ,1967, pp. 295-308.

5 - 38 . A l i s h ous e , Joh n ; Jacobow i t z , H e rbe r t ; and W ark , D a v i d : A

Cloud Ph ys i c s Inve s t i ga t i on Uti l iz ing Skylab D a t a . N A S A

CR- 1 4 7 4 7 4 , 1975.

5-39. Vil levie i l le , A.; and W e i l l er , A. B.: The Possibi l i ty of

Ev a lu a t in g Ver t ical W ind Prof i les From S ate l l i t e Data.

NA S A CR- 1 4 7 4 7 5 , 1 9 75 .

5-40. K ue t tn er , J . P . : Clou d Ban ds in the Earth ' s Atmo sphere : Ob-

s e r v a t io n s an d T h e ory . Tellus , vol. 23, no . 4-5, 1971, pp .

404-426.

5-41. L e M o n e , M a r g r e t A n n e : Th e S t ruc t u re an d D y n a m i c s of

Ho r iz o n ta l Rol l V or t i c e s in the P l a n e t a r y B o u n d a r y L a y e r . J .

A t m o s . Sci., vol. 30, no. 6, Sept . 1973, pp . 1077-1091.

5-42. Marwi tz , J . D. : The S t ruc t u re an d M ot i on of Severe

Hai ls torms. Part I : Superce l l Storms . J . Ap pl . Meteorol . , vol .1 1 , 1 9 7 2 , pp . 166-179.

5-43. Dav ies-Jones , R. P . : Discuss ion of M easu rem ents Ins ide

H i gh - S pe e d T h un d e r s t o rm U p d ra f t s . J . Ap p l . M e t e oro l. , vo l .13,1974, p p . 710-717 .

5-44. S as ak i , Y . K . : M e ch an i s m of S q ua l l - L i ne F orm at i on as S ug-

gested F rom V ar i a t i ona l Ana lys i s o f H our ly S urf ace Obs e r -

vat ions . Prep rint s of the Eigh th Con ference on Severe LocalStorms, American Meteorol . Soc . (Boston, Mass . ) , Oct .15-17, 1973.

5-45. Beebe, R. C. : Large Scale Irr igat ion an d Severe Storm

E n h a n c e m e n t . S y m p o s i u m o n A t m o s p h e r i c Diffusion an d

Air Pol lut ion, Am e r i can M e t e oro l . S oc . (Boston, Mass. ) ,

1974, pp. 392-395.

5-46. Moore , Ri ch a rd K. ; and U lab y , F aw w az T . : T h e R ad ar

Rad i om e t e r . P roc . IE E E , vo l . 57, no . 4, Apr. 1969 , p p .

587-590.

5-47 . Mi t suyasu, A.; and H ond a , T.: The H i gh F re q ue ncy

Spec t r u m of W ind Generated W aves . J . Ocean ograph . Soc .

Jap an , vo l . 30, no. 4, 1974, pp . 29-42.

5-48. Pierson, Wi l l a r d J . : The Theo ry and Ap p l i c a t i ons o f Oce an

W ave M e as ur i ng S ys t em s A t and B e low t h e S e a S ur f ace , on

t h e L and , F rom A i rc r a f t , and F rom S p ace c ra f t . NAS A

CR-2646, 1976.




5-49 . Card one , Vin cen t J .; Y oung , Jam e s D. ; e t al. : T h e Measu re - 5 -51 . Card one , V. J . : Speci f icat ion of the W i nd F i e ld D i s t r i bu t i on

m e nt o f t h e W i nd s Ne ar t h e Oce an S ur face W i t h a i n t h e M ar i ne B ou nd ary L aye r fo r W ave F ore cas ti ng . Re p .

Rad i om e t e r - S ca t t e rom e t e r on S ky l a b . A Join t Meteorologi - TR 69-1 , Geop hys . Science Lab. , New York U niv . , Dec .

ca l Oce anograp h i c an d S e nsor E va lua t i on P rogram for Ex- 1969.

p e r i m e nt S 1 9 3 on Sky lab. NA SA CR-147487 , 1976 .

5-50. Ross, D u n c a n : A Comparison of Synoptic an d Skylab

S 1 9 3 /1 9 4 D e t e rm i na t i ons o f Oce an S ur f ace W i nd s p e e d s .NAS A CR- 1 4 7 5 4 0 , 1 9 7 5 .

2 5 6 S K Y L A B E R E P IN V E S TI G A TI O N S S U M M A R Y



Data Analysis TechniquesF A B I A N C . P O L C Y N , " * K E N N E T H R . PiECH,

btA L L A N S H A P I R O ^

L A R R Y B . Y O R K ,d

A N D A N D R E W E . P O T T E Rd

T E S K Y L A B E A R T H R E S O U R C E S Exper iment Pack-age ( E R E P ) sensors provided a multisensor data

base fo r assessing the use of s tanda rd informa t ion ex-traction techniques as well as for developing new tech-niques. Th e EREP investigators analyzed data from th ep h o t o g r a p h i c , e l e c t r o - o p t i c a l m e c h a n i c a l , a n dmicrowave sensors in ways tha t were appropr ia te to apar t icular ap plic ation . In several instances, the in-vestigators developed improvements in remote-sensinganalysis techniques or provided results that guided th eselection of location of operating bands for fu ture sen-

sors.Because th e space-f l ight performance of the E R E P

sensors dictates to a large degree th e data-processingand analytica l techniques used by individual investiga-

tors, th e in-f l ight performance of the ER EP sensors andth e data analysis techniques used fo r each sensor aresummar ized in this section. Other techniques are dis-cussed in sections 2 to 5 and in appendix D .

O f all the sensors onboard, cameras f i l tered fo rselected wave length bands produced p hotog raphs hav-in g th e best spatial resolution. The analytica l techniquesfo r th e EREP photographic exper iments repor ted inthis section ar e discussed in four general categories:visual analysis of the imagery from different spectralbands and f rom dif fe rent sensors; microdensi tometryand color encoding; multiband image enhancement and

Env i ronmen ta l Research In s t i tu te of Mich iga n .bCalspan Corpora tion.C

U . S . Naval Research Laboratory.d NA SA Ly ndon B. Johnson Space Center .

* Pr incipal Investiga tor .

ana lys is , inc lud ing image d ig i t iza t ion and compute rtechniques; and data processing that provided input

pa ramete rs fo r Earth resources management models.Th e EREP opt ica l -mechanica l scanner providedmul t ichanne l compute r -compa t ib le tapes tha t pe rmit -te d machine enhancement of surface features based onspectra l signature analyses. The techniques used to en-sure acceptable recognition accuracies include d mu lti-band comparisons, ra tio processing, spectra l classifica-tions based on sta tistica l tests , mi xtu re processing, andsignature-extension schemes. A n inf ra red spec t romete rprovided high-spectra l-resolution data in the vis ible andinf rared bands from preselected test sites so t ha t at-mospheric corrections and surface signatures could bedeveloped.

Act ive and pass ive microwave sensors, opera t ing a tth e longest wavelengths used by E R E P sensors, pro-v i d e d c o m p u t e r - c o m p a t i b l e - t a p e ( C C T ) d a t a f ro mw hic h informa t ion about th e a tmosphere , th e surfaceroughness, th e soil mo isture , and the shape of the Ear thcould be de te rmined . To achieve the f u l l pe r f o r m a nc epotent ia l of the altimete r , specia l techniques weredeveloped to de te rmine th e antenna poin t ing angledirectly from th e radar re turn and to ca lib ra te range andpower outp ut for pulsewid th- and beam width - l imi tedc o n d i t i o n s . T h e i n t e r p r e t a t i o n o f da ta f r om th er a d i o m e t e r / s c a t t e r o m e t e r ( R A D S C A T ) r e q u i r eddifferent sta tist ica l methods of analysis for ver if ica tion

and correction. Rigorous methods fo r comput ing oceanemission at microw ave f requenc ies fo r different phy s i -cal conditions were developed an d used to separatevarious physical parameters from th e radiometer datacharacter istics.

257



Th e data analys is techniques provided for the con-

vers ion of sensor da ta in to meaningful appl i ca t ion in -forma t ion such as numbers , t hemat i c maps , and b ound -

aries from which decis ions could be made , ac t ion t aken ,and new programs in i t i a t ed . In general , this t ransforma-

t ion could not be a c c om pli she d w i t ho u t s uppo r t i ng in -

forma t ion , sur face t ru th , or a f r a m e wor k of m ode lana lys i s . The de ve l opm e n t of sui t ab le models andf rameworks for input t ing th i s new form of da ta sup-

pl ied by spaceborne sensors is one of the m a i nchal lenges to the m a x i m um u t i l i z a t i on of remote-sens-in g t echniques .

SENSOR F L IG H T P E R F O R M A N C E

T h e ER EP inves t iga tors def ined the i r ex per imentson the as sumpt ion tha t predic ted sensor pe r f o r m a nc eleve l s would be achieved dur ing f l ight . Therefore, an

impor tant t a sk dur ing th e E R E P da t a passes was to testth e sensors to determine their actual opera t ional per-

f o r m a nc e .Sensor performance w as evaluated in three d i f fe rent

areas: (1 ) func t iona l pe r form ance (e.g ., camera shut t e roperat ion an d a n t e nna m ove m e n t ) , (2) geometric per-formance (e.g., spat ia l dis tort ions in the imagery , poin t -

ing accuracy of the a n t e nna ) , and (3) rad iomet r i c pe r -formance (e .g . , r ad iomet r i c accuracy and prec i s ion) .General ly, only th e flight data collected for the E R E PPrincipal Invest igators were used for the sensor per-formance eva lua t ion; however , for the l una r or deep-space cal ibrat ion s tudies , a res t r i c t ed amount of data

w a s c o l l e c t e d s pe c i f i c a l l y fo r sensor p e r f o r m a n c eevaluat ion. Detai led discuss ion of the pe r f o r m a nc e andengineering evaluat ion of each sensor is publ i shed in anN A S A i n t e r na l doc um e n t

1and summar ized by Potter et

al. (ref. 6-1). A b r i ef s um m a r y of the resul ts of the sen-sor eva lua t ion is presented fo r each sensor (app . A ).

Multispectral P ho tog r a ph i c C a m e r a

Th e M ul t i spec t ra l Photographic C amera (S190A)consisted of s ix bores ighted camera s ta t ions , four withspec t ra l f i lt e r s and b l ack -and -w hi te f i lm, one wi th h igh-

40S c a l e , k m

i-

Sk y lab Program Ear th Resources Ex pe rim ent Package SensorPerformance Reports: vol . 1 (S190A), vol . 2 (S190B), vol. 3 (S191) ,vol. 4 (S192), vol. 5 (S193), an d vol . 6 (S194). Mart in Mariet ta Co. ,JSC-05528, 1974.

FIG U RE 6 -1 .—Co l o r - i n f ra red i m a g e ry of the Im per i a l Va l l ey an dth e Sal ton S«a , Cal i fornia (S-73-1227).

resolut ion color f i lm , and one w i t h color - inf ra red fi lm.An exam ple of imagery f rom the co lor - in f ra red cameras t a t i on show ing the Imp er ia l Va l l ey and the Sa l ton Sea

C a l i fo rn ia , is i l lus tra ted in figure 6-1. This figure is ane n l a r g e m e n t ; one ent i re S190A frame covers a 163-km-square area . Vegetat ion is del ineated by red tones . Thesame scene , pho tograp hed w i th the h igh- reso lu t ion co l -or camera s t a t ion , is s h o w n in figure 6-2. To de m on-s tra te th e reso lu t ion capab i l i ty of the S190A system,t h i s scene w as enlarged. The l i m i t of resolu t ion can beseen in figure 6-3. The measu red reso lut ion ca pa b i l i ty ofthe cam era for th i s fi lm was app rox ima te ly 27 m perl in e pair fo r high-cont ra s t s i t e s a nd a p p r o x i m a t e d th eva l ue expected from p ref l ig h t tes ts . The regis t ra t ionca pa b i l i ty of the b l a c k - a nd -wh i t e i m a ge r y is i l l us t ra tedin figure 6-4, a composi te generated by superimposing

enlarged images f rom three b l ack-and-whi te camera s t at ions for the Imperia l Val ley scene (figs. 6-1 and 6-2).The images can be regis tered to w i t h i n bet ter th an 20 mon the grou nd , app rox ima te ly the va lue expec ted f rompre f l igh t tes ts . The S190A camera was a radiometric

2 5 8 S K Y L A B E R E P I N V E S T IG A T I O N S S U M M A R Y



> "

F I G U R E 6-2.—The Im per i a l V a l l ey , Ca l i fo rn i a , pho t o g ra phed wi t hhigh-resolut ion color f i lm (H • m a g n i f i c a t i o n ) .

camera in tha t film density could be re la ted quan-t i tat ive ly to the intens i ty of radiat ion incident on thelens . In -f l ight measurements us ing th e ground si tes an d

the Moon establ ished radiometr ic cal ibrat ions accurateto w i t h i n ±3 0 percent .

Earth Terrain Camera

Th e Ear th Terrain Camera (S190B), a single cameras ta t ion , was designed to demon s t r a te the a pp l ica t ion ofhigh-spa t i a l - reso lu t ion i m a g e r y in E a r t h resource sur -veys a nd n o r m a l l y w as operated with ei ther high-resolution color or b l a c k - a n d - w h i t e f i lm . A n S190B im -age m a d e with h igh - r eso lu t ion co lo r film cover ing a109-km-square area over Phoenix, Ar izona, is shown in

figure 6-5. The Sun City Development area , which i sused to dem onstrate the resolution capa bil i ty of the

camera , is visible in the u p p e r left center of the pho to -graph. Figures 6-6 to 6-8 show successively greateren la rgements of t h i s same area. Th e resolution l i m i t of

th e camera system w as a p p r o a c h ed at the m a g n i f i c a t i o ns h o w n in figure 6-8. The measured resolution l i m i t s

w er e a p p r o x i m a t e l y 9 m per l ine pai r f rom b lack -and-w h i t e f i lm. Per formance of the camera w as w i t h i n ex -pected l imi t s for al l p a r a m e t e r s .

I n f r a r e d Spectrometer

The Inf r a red Spec t rometer (SI91 ) measured ther ad i a t i on f rom a 0.46-km-diameter area on the E a r t h inthe ran ges 0.4 to 2.5 /u rn and 6.6 to 16 /im. The telescopew h i c h c o l l e c t e d a n d t r a n s m i t t e d l i g h t t o t h espec t rometer cou ld be pointed by a c rewman a tpreselec ted s i tes below the spacecraf t . Photographs of

th e scene th rough th e te lescope recorded po in t in g ang leand t ime so that the posit ion of a measured s i te on thegr ound cou ld be computed .

The S191 was tested by mea sureme nts of cal ibrate d

groun d si tes and areas of the Moon. Typical ground si tespectra taken with the spectrometer system are shownin figure 6-9.

Careful analysis of the spectral data indicated thatt h e i n s t r u m e n t p e r f o r m a n c e w a s w i t h i n p r e f l i g h tspecif icat ions in the ref lec t ive range, except at the b lueend of the spectrum (0.4 / im ), whe re excessive off -ba ndr ad i a t i on a p p ear ed . W h en v i ew i n g s i m i l a r scenes , rela-t ive values in the thermal emissive par t of the spectrumwere wi th in expec ted tolerances, but the absolute ra-

diance values were incorrec t b y var iab le amountsequiva lent to a m i n i m u m of 1 K to several kelvins.P o s t f l i g h t a n a l y s i s o f d a t a f r o m t h e b a c k u p

spec t rometer f lown on a hel icop ter ind ica ted tha t th eprobable cause of this er ror was an incorrec t t ransmis-sion coeff ic ient for the d ichro ic beamsp l i t te r , wh ichdiv ided the ref lec t ive and emissive par ts of thespec t rum.

M u l t i s p e c t r a l Scanner

The M ul t i spec t r a l Scanner (SI92) p rov ided imageryin 13 spectral b a nds ran gin g from the blu e (0.4 /-im) tot h e t h e r m a l - i n f r a r ed ( 1 2 . 5 / u r n ) p o r t i o n s o f t h ee l e c t r o m a g n e t i c s p e c t r u m . T h e i m a g e d a t a w e r e

recorded on magnetic tape fo r later analysis by h igh -speed computer s . A n ex a m p l e of data f rom th e S192 issho wn in figure 6-10. Three of the 13 bands (2 inf rar edand 1 green) were super imposed to make this image.Agricul tura l features, such as circular i r r igated f ields ,

D A T A A N A L Y S I S T E C H N I Q U E S 25 9



r i ,• "M• •••• -

~ -A mI.J .1P •

S c a l e , k m

FIG U RE 6 -3 .—En l arg ed area of Imperia l Val ley , Cal i fornia , photographed wi th high-resolut ion color f i lm.




0 10

Scale, km

FIGURE 6-4.—Composi te photograph of b lack -and-whi t e imagery of Imperial V alley, Cali fornia , generated by superimposing enlarged imagesfrom three black-a nd-w hi te camera stat ions, sho wing regist rat ion capab i li ty .

D A T A A N A L Y S I S T E C H N I Q U E S 2 6 1



%. Hf:

i - > . * & V f c

2 0 y

S c a l e , km /

nGURE 6 -5 .—An S190B image made wi th high-resolut ion colorfilm o v e r P hoen ix , A ri z o n a (1.56 x en l a rg em en t ) (SL3-86-011).

can be seen clear ly in the imag ery. Close exa mina tion offigure 6-10reveals that the unfil tered imagery containsa noticeable degree of noise. To determine the effects ofthis noise on the co mp uter analy sis of this ima gery, the

small outl ined area w as subjected to computer analysis.Th e results of this analysis are show n in figure 6-11.

Th e analyzed area is out l ined on an S190 pho tog r a ph onthe r ight, and the results of the computer classif ica tionare show n on the left. Agr icul tura l and other featureswere classified with an acceptable accuracy (greatertha n 90 percent) . The noise in the imagery did not havea major effect on computer classif ica tion; apparently,some of the noise w as correlated between th e differentspectra l channels. However , th e noise w as larger thanhad been expected on the basis of pre f l ight measure-ments . Consequent ly , a noise analysis w as per formed,and tw o major types of noise were found : high frequen-

cy (2=20 kHz)and low frequency (^20 Hz). In severalchannels, high-frequency noise a t discrete frequencies

$ * < ' &" - Stf«* * ~. 5»

sv

FIG U RE 6-6.—Enlargement (3.8x m a g n i f i ca t i o n ) of S190 imageover P h o e n i x , Arizona.

FIGURE 6-1.— Enlargement (9.45 x magnifica t ion) of S190 imageover Sun Ci ty Development area of P hoen ix , A ri z o n a .

2 6 2 S K . Y L A B E R E P I N V E S T I G A T I O N S S U M M A R Y



FIGURE 6-8.—Enlargement (39.4 x magnif icat ion) of S190 image over Su n City Development area of Phoenix , Ar izona .




H20 H20 H 2 O . C 0 2

10-V

-

FIGURE 6-9.—Typical S191 spectral data showing peaks for oxygen (O 2) , water vapor (H 2O), carbon dioxide (CO 2) , ozone (Oj) , and methane(C H 4).

F IGUR E 6-10.—S192 Mult ispect ral Scanner imagery of Hol t C oun ty , Nebras ka (S-73-1510).




F I G U R E 6-11.—Com puter an alys is of s tud y area ( rec tangle in f ig. 6 -10) in Hol t Co unty , Nebraska (S-73-2839).

w as observed. This noi se produced he r r ingbone pa t -terns in the imagery . Because th e noise occurred a tsharp, wel l -defined frequencies , i t was poss ible toremove th e noise b y c om pu t e r a na l y s is ( m a t he m a t i c a l

filters).Th e l ow-f requency noi se w as most not iceable in the

t he rmal - in f ra red c ha nne l a nd p r oduc e d he a vy b a nd i ng( random noi se ) in the image. This imagery was no tusefu l for photo in te rpre ta t ion because the bandingobscured sur face fea tures . Consequent ly , ma themat i ca lfilters and every-sc an ca l ibrat i on data were used tom i n i m i ze or r e m ove th e noise.

An exam ple of the rm a l imagery i s i l l us t ra ted infigure 6-12 . Low-f requency noise w as present beforedata process ing; after process ing, th e l ow- f r e q ue nc ynoise h ad been f i l tered ou t . Im pr ove m e n t in the qu a l i ty

of imagery for photo in te rpre ta t ion i s ev ident .

The the rma l imagery acqui red on the f i r s t two mis -

s ions was acceptable for some app l i ca t ion s but not forothers . As a result , the detectors f low n on the S kyl ab 2a nd 3 m i ss i ons w e r e r e p la c e d w i t h a n i m p r ove d t he r m a l

detector by the S kylab 4 c r e wm e n . The r m a l i m a ge r yfrom the Yuma, Ar izona , reg ion ( f ig . 6 -13) was ob -

t a ined w i t h th e i m pr ove d t he r m a l de t e c t o r . A subs tan-t ia l i m p r o v e m e n t is e v i de n t in the image q ua l i ty pro-duced by the de tec tor. The radio me t r i c pe r fo rm anc e ofth is t he rm a l de tec tor w as such tha t t empe ra tured i f f e r en ces of a p p r o x i m a t e l y 0.8 K we r e e q u i va l e n t to

detector noise .

D u r i n g in i t ia l in - f l ight checko ut and opera t ion ,diff icul t ies with the manua l a l inement and focus ing ofr ad i a t i on on the detectors were encountered. In addi-

t i on , some of the b a nds had an excess ively smal ldynamic range . Therefore , cont ingency a t t enua tors




Befo re process ing

Af te r process ing

FIGU RE 6-12.—Effects of data processing of S192 M u l t i s p e c t r a l

Scanner t he rm a l i m a g e ry (S-74-3154).

were ins ta l led by the c r e wm e n . A smal l percentage ofdata w as lost because of these prob lems . A ll other per-formance fac tors of the sys tem (band-to-band regis t ra-tion, geom etric resolut ion, radiome tric cal ibra t ion, e tc .)we r e w i t h i n th e l imits expected from th e pref l ightcal ibrat ions .

M i c r owa ve Ra d i o me t e r / S ca t t e ro me t e r and Al t imete r

T h e M i c r o w a v e R a d i o m e t e r / S c a t t e r o m e t e r a n dAl t imete r (S193) operated at the K.£-band (2.2 cm )wave length in t h ree d i f fe rent modes: as a passiveradiomete r , measur ing th e microwave energy emi t t edby th e E a r t h ; as an act ive sca t t e rometer , w h i c h sen tm i c r owa ve pulses to the E a r t h and measured th e in ten-sity of the re turn echo; and as a rada r a l t imete r . A llthese func t ions sha red th e same antenna , which w asgimbaled to permi t s canning of the E a r t h in various pat -

terns . Th e antenna func t ioned acceptab ly dur in g theSkylab 2 mission an d mo s t of the Skylab 3 mission;

however, near the end of the Skylab 3 mission, the ant enna began scanning er r a t ica l ly . Ear ly in the Sky l ab

miss ion , th e crewmen were ab le to restore th e a n t e nnscan in one d i rec t ion by m echan ica l ly p in ning i t in one

ax i s and by m akin g mo di f i ca t ions to the e l ec t ronic c i rcu i t s . However , S kylab 4 da ta proved to be anomalou

and very l imi ted amounts of the da ta were recoverab lefo r th e inves t igators .

Analys is of rad iomete r pe r formance indica ted tha

emi t t ed rad iant power was measured wi th an accuracyof a t leas t 4 percent (corresponding to a brightness-tempera ture accuracy of ±7 K) and wi t h a prec i s ion of aleast 2 percent (o r ±1.5 K) for typ ica l ground scenes

The s c a t t e r o m e t e r p e r f o r m a n c e showed t h a t the

reflected s igna l was measured w i th in an accuracy of 4perce nt for typical ground scenes , with a precis ion of a

l eas t 2 pe rcent . W i th th i s accuracy and p rec i s ion , thescat terometer was capable of measuring reflected s ignals tha t varied in am pl i tud e by a factor of greater tha n

10 000:1.Al t imete r pe r f o r m a nc e w as measured f rom ana lys i s

of the da ta ob ta ined over regions wi th known sur facecontours . Th e accuracy of the a l t i t ude m e a s u r e m e nw as ±7 m w i t h a precis ion of ±1 m.

W ith the except ion o f the antenna , a l l pe r formanceaspects of the SI93 dur ing th e Skylab 2 and 3 missionsequaled or exceeded predicted values .

FIGURE 6-13 .—Imagery from th e Yu m a , A r i z o n a , region obtainedwi t h th e improved S192 thermal detector (S-74-23477).




1 . -Ban d Radiomete r

The longest wavelength (21 cm) sensor onboard theSkylab vehic le was the L-Band Radiomete r (S194) ,whi c h measured radiant energy from an a pp r ox im a te ly124-km-diameter area of the Earth. Effective measure-

me nt s were l imited to a 111 -km- wide swath c enteredabout th e nadir poin t . The per formance fac tors of mostinterest fo r th is pass ive microwave sensor were its an-tenna pa t te rn , poin t ing accuracy , and radiometr ic ac -curacy .

Compar ison of predicted and observed signals fromwell -defined surface features were used to def ine th eS194 antenna pa t te rn and poin t ing accuracy . Both thesefactors were wi th in a few percent of predicted values.R a d i o m e t r i c p e r f o r m a n c e w a s de te r m ine d f r o m

measurements of the Sahara Deser t , wh ere large sand yareas tha t have u niform emiss iv ity and tempera ture ex -ist . A precision of approximately ±0.2 K and an ac-

curacy of app roxi ma tely ±1.7 K at 285 K were found .

TH E S190A A N D S190B PHO TOG RAP HICI M A GI N G S E N S O R S

The Sk ylab Program provided a uniqu e opp or tuni tyto use photographic imagery in Earth resources in-vestigations. Investigators were able to analyze high-resolution photographs processed unde r carefully con-trolled conditions, with known camera performancecharacteristics, and with a wide range of film and

spectral filter combina t ions . The investigators usedboth sophistica ted data analysis and s tanda rd photoin-terpreta tion techniques. The advanced techniques in-c lude d c om pa r i son o f im a ge in f o r m a t ion a m ongspectra l bands, precise image densitometry, and multi-band analysis and enhancement techniques. The ap-plicat ion of these sophistica ted analysis techniques le dto signif icant results that ar e discussed in the precedingdisc ipl ine summary sections.

Almost all the analysis techniques an d results ar ebased on two key properties of the Skylab photographs .A brief descr iption of these properties will assist in theunder s tand ing and apprecia tion of most of the tech-

niques developed during the photographic exper iments .First, the Skylab photographs provided investigators

with i n f o r m a t ion in m a ny w a ve l e ng th , or spectra l ,regions. The spectra l data were obta ined from fil teredb l a c k - a nd -wh i t e f i lms or from i n f o r m a t ion in the layersof multiband f i lms, such as color and color- infraredfilm. In the case of filtered im age ry, the spec tral ban dswere defined by the com binatio n of the wav eleng th

transmitted by the f i l ter (filter spectra l bandpass) andth e wave length sensi t ivi ty of the film (film spec tra l sen-s i t ivi ty) . For the m ul t ib a nd films, the spectra l bandswere determined primari ly by the spectra l sensit ivity ofthe individual f i lm layers. The investigators extractedthe spectra l information from th e mul t iband imageryby sepa ra t ing th e informa t ion in the indiv idua l filmbands throug h a f il ter ing process. Thus , by using eith er

th e fil tered or the m ul t ib a nd im a ge ry , th e Skylab in -vestigators had a w ide varie ty of high- resolu t ion photo-gr a ph i c images fo r Earth resources investigations.

Second, the S kylab photog raphic exper iment packagewas designed to enable use of the cameras to measure

the am ount of energy ref lected from the E arth. In otherwords, th e Skylab cameras could be used as imagingphotometers (devices that measure incident energy) .T hus , investigators were able to de te rmine th e energycoming f rom any pa r t of the photographic scene bycareful measurements of the density of that par t of theimage on the exposed fi lm.

Each roll of film had a sensitometr ic control str ip(fig. 6-14) that could be used by the investigator torela te photographic density to the energy that exposedthe film. Each control strip consisted of a set of filmareas exposed with known amoun t s of energy. A com-parison of the density from a Skylab scene with the

same density on the co ntrol str ip provided a measure-m e n t of the energy incident a t the f i lm plane in thespacecraf t . Also, because the effects of the cameralenses and shutters on exposure energy had beencarefully measured, camera effects could be removedfrom the image data . The photographic image datacould be processed to obtain an accurate measure of theenergy reaching th e spacecraf t f rom any por t ion of thepho tograph ic scene. Thus, the investigators not onlyh ad high- resolu t ion pho tograph s tha t enhanced te r ra inand resource features, they were a lso able to extract ameasurement of reflected energy in each spectra l bandbeing studied and to compare the energy differences

among the spectra l bands. The abil i ty to measureenergy values in the different spec t ra l bands was of fun-




FIGU RE 6-14.—E xample of a sensi tometric contro l s t r ip for color f i lm. Each step, or square , has been exposed b y a di ffer ent amo unt of l i g h t

en e rg y . B y m ea su r i n g th e den s i t y of each step, invest igators ob ta ined th e re la t ionship between image densi ty and exposure of the f i l m .

d a m e n t a l i m p o r t a n c e to severa l n e w t e c h n i q u e sd ev e l o p ed d u r i n g t h e p h o t o g r a p h i c ex p e r i m en t .

T h e da ta ana lys i s techn iques developed f rom th eSI90 pho tograph ic exp er imen t can be g rouped in to four

categor ies: (1) techniques ar is ing f rom the app l icat ionof conven t iona l pho to in terp re ta t ion met h o d s to theu n i q u e data fo rmat p rov ided by the S kylab photo-graphs, (2) techniques evolving f rom var ious forms ofimage dens i tomet ry , (3 ) t echn iques developed frommul t iband spec t r a l enhancements or analyses , and (4)

techn iques in which Sky lab pho tographs p rov ided aun ique model inpu t fo r Earth resources analysis .

Photointerpretation Tech n i q u es

Conven t iona l pho to in terp re ta t ion techn iques p r in -cipal ly involve visual evaluation of shapes and p a t t e r n son the pho tograph ic image (append ix D) . The shapesand p atterns a re def ined b y the tonal and tex tural var ia-t ions wi th in the scene. Interpreters evaluate the pat-terns discr iminated on the basis of the i r under s tand ingof , and exper ience wi th , the phys ica l processes u n d e rstud y. Many successful app l icat io ns of such conv en-t ional photointerpretat ion analysis can be found in thei nd i v i dua l d isc ip l ine sections of this report. The new ap -

p roach fo r Skyla b visual analysis techniques is basical lyan ex tens ion of the conven t iona l p ho to in terp re ta t ionm e t h o d s to inc lude , o r take advantage of , the u n i q u e

character is t ics of Sky lab pho tographs ; n amely , th eperspective achieved f rom space (large areal view with

high resolution), a wide selec t ion of spectral ly f i l teredimages , and the ph o tograph ic fo rm at f rom w hich v isua lcompar i sons can be ma d e .

Each f r a m e of S kylab imag ery covers a large area; th e

S190A pho tographs cover a p p r o x i m a t e l y 160 km oneach side, and the S190B photographs cover approx-imate l y 110 km on each side. A h igh -a l t i tude aircraf t

f l y in g at 15.24 km w i t h a s tandard 150-mm focal l eng th ,230-mm fo rmat mapp ing camera would r equ i r e 50p h o t o g r a p h s to cover fully an area 160 km on each side,assuming per f ec t flight l ines and no over lap betweenp h o t o g ra p h s . W h en a s t a n d a r d a m o u n t of p h o t o g r a p h i cover l ap i s al lowed, th e n u m b e r of pho tograp hs r equ i redto cover the 160-km square increases to more than 200.A prodigious effor t wou ld be required to correlate thesep h o t o g r a p h s so tha t an interpreter could recognizelarge-scale effects occurring over 16 to 160 km.

Th e Skylab pho tograph ic exper iment r emoved th i slogistical obstacle by p r o v i d i n g h i g h - q u a l i t y , h i g h -resolut ion photographs cover ing large areas . Photoin-

terp re ter s cou ld thus eva lua te phenom ena a t phys ica lsca les p rev ious ly una t ta inab le . Fo r ex a m p l e , figure 6-15is an S190B color photograph of the Pacific Ocean nearPo in t Arena in nor thern Cal i fo rn ia . Th e whi t i sh tonesin the w ater are caused by sedim ent of varying con-centrat ions. A s tudy of this photograph by Pirie andStel ler (ref . 6-2) provided information on the occur-rence of u p wel l in g s and location of coastal current thatwould have been impossible f rom aircraf t pho tographs .

M a p p i n g f rom a i r c r af t pho tographs would have re -quired a degree of fiight-line accuracy tha t would havebeen extremely diff icul t to ach ieve over th e ocean. Th eocean has no l a n d m a r ks w i t h w h i c h to sight a flight l ine

or to or ient photographs. Also, aircraf t coverage wouldh a v e required hours of f ly ing, dur ing wh ich the cur r en tscould change or l ighting cond it ions could vary . Thevar i a t i on in l igh ting cond i t ions would cause ana lys i sdifficulties because current s tructures w ere extrac ted on




'I

0 10

S c a l e , k m

F I G U R E 6-15.—The eddy pat tern at Point Arena (nor thern Cal ifornia) is vis ible as longshore currents mo ve suspended sediments in as ou ther ly d i r ec t ion . T h e presence of offshore swir l an d boundary patterns indicates a s low-moving Cal ifornia Current . Upwel l ings ( I) and cur-

rent direc t ions (ar rows) ar e indicated. Five fingers, or scalloped patterns, ar e present offshore on this color photograph (SL4-92-333).

D A T A A N A L Y S I S T EC H N I Q U E S 26 9



th e basis of tonal var ia tion over th e ocean. Finally , eachaircraft photograph would have brightness changesf rom s ide to s ide ac ros s th e forma t caused b ydifferences in angles of i l l um ina t ion and ref lection.These brightness changes would a lso have contr ibutedto analysis difficulties. Th e problems of f l ight - l ine ac-

curacy, t ime varia tion, and tonal or br ightness f luctua-t ions were minimized by Skylab photographs .

Barnes et al. (ref. 6-3) evaluated the usefulness ofEREP da ta for mapping snow cover . Accura te snow-cover mapping is c ruc ia l fo r runof f predic t ion and wate rmanagement . These investigators determined that S190color and color - inf ra red photographs could be used tom ap snowpack ex tent more accurately than could im -ages provided by any other spacecraf t or ai rcraf t

sys tem. A key element in the S190 mappin g cap abil i tywas the perspective a ttr ibutable to large-area coverage.Figure 6-16 depicts snowline regions in centra l Arizonadetermined from an S190B photograph and from a con-

current aer ia l snow survey. The aer ia l survey snowlineis considerably less deta iled than th e Skylab-delineatedsnowline, and the position determined from th e aerialsurvey does not fit the topography as closely as theSkylab snowline. The accuracy of runoff prediction isclosely rela ted to the accuracy of snowline ma pp ing .

Image analysis techniques using photointerpreta tionof image patterns were signif ican tly extended in theSkylab photographic exper iment by inc luding com-parisons of photographic image pa t te rns wi th pa t te rnsfound on nonph otographic imagery , such as those f romthe S192 Multispectra l Scanner . Skylab investigatorswere thus able to ex trac t addi t iona l informa t ion on such

problems as the detection of oceanic up we ll ing regionsfo r f ishery resources, the determ ination of ver tica l sedi-m e n t distr ibution in coastal waters, th e detection ofmelting snow regions for runoff prediction, and thedifferentiat ion of water droplet c louds from snow.

Szekielda (ref. 6-4), for example, used SI90 colorphotographs to study ocean color changes as possibleclues to the location of an up well ing. As discussed insection 5, upwelled waters afford an excellent mediumfo r the growth of f ish. Monitor ing the location of up-well ing regions f rom space is thus ex t remely imp or tan t .

Photoin te rpre ta t ion of red and green spectra l bandsproved useful in determining the vertica l distr ibu tion of

suspended sediments (ref. 6-2). Because penetration ofwater by red wave lengths is sma l l , an image in the red

spectra l band depicts only near-surface information.W ater pen etra tion in the green spectra l region is greaterthan in the red, and an image in the green spectralregion provides deta iled information on subsur facesediments. The d iscr im inatio n of such surface and sub-surface effects is depicted in figure 6-17.

Barnes et al. (ref. 6-3) developed a t e c hn iq ue for theautomat ic d isc r imina t ion be tween snow and wa te rdrople t c louds by com par ing SI92 imagery in the visiblespectra l region to tha t in the m idd lein frared (1.6 to 2.4^.m) region. In the latter spectral range, th e ref lectanceof snow is a lmost zero, whereas water droplet c loudshave a high ref lectance. A compar ison of the vis ib lespectra l region, in wh ich both types of objects have h ighreflectance, with the 1.6- to 2.4-fj.m region thus permitsd isc r imina t ion . The d i s c r im ina t ion t e c hn iq ue is of par -t i c u l a r s ign i f i c a nc e f o r a u tom a t i c snow m a p p in gbecause cloud disc r imi natio n has been recognized as aser ious hindrance to eventual machine processing of

satellite data for snow-cover mapping.Similarly, Piech et al. (ref. 6-5) demonstrated that a

comparison of red (0.6 to 0.7 /xm) and near-infrared(0.8 to 1.0 f j . m ) spectra l bands w as useful in different ia t -in g a tmosp her ic turb id i ty tha t occurs over a large lakef rom the turb idit y that occurs w ithi n the lake. The tech-n iq ue is par t icu la r ly useful in account ing for the effectsof very l ight, wispy clouds or haze. In the near- infraredspectra l region, a lake without high sediment load will

appear black, whereas a cloud or haze effect will main-ta in a signal or pattern similar to i ts pattern in the redspectral band. A comparison of the two spectra l bandsthus pe r m i t s d i s c r im ina t ion b e tw e e n a tm osphe r i c

effects and lake effects; this disc r imina tion is imp ortantin m e a s u r i n g p a r a m e t e r s such a s t u r b i d i t y a n dch lo rophy l l concentra tion.

A com parison of visible and nea r- infrared bands h asalso prov ed useful for detecting snow cover in a meltingcond ition (f ig. 6-18). Such snowmelt inform ation is par-ticularly needed in regions where signif icant portion s ofthe snowpack can melt within a few days, or evenhours. A mel t ing snowpack decreases in appa rent ex-tent when viewed in the visible and near- in frared bandsbecause of a decrease in the reflectance of meltingsnow. A comparison of visible and near- infrared bandsyields a measure of the melt ing condi t ion of the

snowpack .

27 0 S K Y L A B E R E P I N V E S TI GA T IO N S S U M M A R Y



CA N ION

'

£

- f i t f m a e Lo>

' ,

0 10

Scale, km

FIGU RE 6-16.—Portion of U.S. Geological Survey topograph ic map showing central A rizona. Thin b lack lines indicate boundaries of snowareas with di ffe r ing reflectances as mapped from an S190B pho tograph; H, M, and L indica te high, m edium , and low reflectance, respectively.

Heavy black l ine indica tes snow boundary as depicted on aeria l survey snow chart.

D A T A A N A L Y S I S T E C HN I Q U E S 27 1



0 10S c a l e , k m

'*

FIG U RE 6-17.—Example of the use of dif ferent spectral bands in determining the vert ica l d ist r ibut ion of suspended sediments in coasta l w aters

off Point Reyes, C al i fornia , (a) Gree n band (0.5 to 0.6 / itm) displays deta i led i n f o r m a t i o n including the effects of water penet ra t ion (SI.4-78-071). (b) Red band (0.6 to 0.7 Aim) shows surface deta i l wi thout in terference from subsurface sediments (SL4-77-071).

D e n s i t o m e t r i c Analysis Techniques

A pho t o i n t e r p r e t e r is l imi ted in the abi l i ty to dis-c r im ina te tona l d i f fe rences w i th in an image. The l imi ta -tion arises because of visual and psychologica l con-straints in qu an t i f y in g contras t differences betweenpoints of an image tha t are separated or be tween poin t sof an image lying in an area of changing image t ex ture .Several Skylab invest igators found i t des irable to quan-tify impor tant dens i ty or exposure changes occur r ing

wi th in t he photographic s cene by us ing va r ious formsof image densi tometry.

S om e i nve s t i ga t o r s ( r e f . 6 -5 ) u s e d m a c r ode n -s i tometers to measure densi ty values over a large spoton a photograph , typ ical ly app rox im a te ly 0 .5 mm indiamete r . A den s i ty reading on a 0.5 -mm -diamete r spotcovered a ground a rea of 1.5 km in diamete r on SI90Aphotographs and 0.5 km in diameter on S190B photo-graphs . O ther invest igators (refs . 6-2 and 6-5) usedmicrodens i tomete rs to measure densi t ies over spot

2 7 2 S K Y L A B E R E P I N V E S T IG A T I O N S S U M M A R Y



d iame te r s o f a pp r ox i m a t e l y 25 / u r n c o r r e s pond i ng to a

gr ound d i m e ns i on of 75 m in diamete r on S190A ph oto-g r a phs and 25 m in diamete r on S190B photographs .The m icrodens i tomete rs were used in a ma nner s imi l a rto the use of a mac roden s i tomete r , to measure the den-s i ty of specif ic imag e spots , or to scan the image to pro-

v ide a t race, or record, of dens i ty va lues f rom whichcontours or shapes could be drawn.

An othe r method used for image dens i tom et ry wasthe appl i ca t ion of co lor -encoding devices , in which ate levision vid icon scans t h e pho t og r a ph a nd c onve rt s

th e l ight s ignal to dens i ty va lues . Th e dens i ty range ofth e scene is then divid ed electron ical ly into 10 or 20ranges of densi ty. Each densi ty range is ass igned an in-d i v i d u a l color, a n d t h e p h o t o g r a p h i c scene i sredisplayed on a color te levis ion screen with the photo-g rap h ic densi t ies encoded as colors . The resul t ing colorp a t t e r n s c a n t h e n b e i n t e r p r e t e d a s r e p r e s e n t i n gdif ferent types of trees or differing sediment concent ra -

t ions , depending on the prob lem under inves t iga t ion .Dens i tomet ry of indiv idua l l ayers of the mul t iband

color or color-infrared f i lms was accomplished by twomethods. In one method, a filter t ransm i t t ing l ight f romone f i lm l ayer w as inserted into th e dens i tomete r sothat densi ty values were measured fo r only tha t film

b a nd o r l ayer . In the second method, a b l a c k - a nd -wh i t ec o p y , or s epa ra tion , of the inform at ion on one f i lm

layer was made throu gh a fi lt e r . Dens i tomet ry was thenpe r f o r m e d on the b l a c k - a nd -wh i t e c opy of the scene.

Regardless of the techniques used, invest igators wereab le to ob ta in spec t ra l -band informat ion f rom the

m u l t i b a nd f i lms and to a p p l y these data to their

resource invest igat ions successful ly.Th e densi tom etric analy s is techniqu es were app l ied

not only to Skylab photograph s , but to va r ious enhance -ments of the photographs such as ra t io com bina t ions offilm l ayers (ref . 6-5) . Appl icat ion of densi tometry tos uc h m u l t i b a nd enhancements is discussed in section 3and in the fo l lowing subsect ion. Densi tometry of the

original photographs proved mos t usefu l in wa te r -quali ty s tudies rela ted to coas ta l dynamics and sedi-ment t ranspor t , and in l and use studies such as t imberdif ferentia t ion a nd class if icat ion.

Baldridge et al. ( ref . 6-6) appl ied color encoding ofcolor and c olor - inf ra red imagery to t imber d i f fe rent i a -

t ion and analys is . Color encoding was successful ly ap-pl ied to t imb er ma pping , d i f fe rent i a t ion of ha rdw ooda n d s o f t w o o d stands, a n d e v a l u a t i o n o f t i m b e rmatur i t y . The inf ra red-sens i tive l ayer of color - inf ra red

film proved mos t s ens i t ive a n d va l ua b l e fo r t i m b e rd i f f e r en t ia t io n . Figure 6 -19 conta ins examples of suc-cessful de l inea t ion of t imber m a tu r i ty f rom S190B col -or- infrared pho tographs . Thi s figure shows color encod-in g of a sample a rea in M a hon i ng C oun t y , O h i o , c on-taining only three s t ages of s t and m a tu r i ty . The a rea

was 1 of 16 samp le a reas in whi c h m a c h i ne de t e r m i na -t ion of s t and m a tu r i ty from S190B ph otog raph s was un-der taken . Forest management pe rsonne l conf i rmed th eva l id i ty of the class if icat ion based on the color-encod-in g techniques in al l the sample s i tes .

N u m e r o u s i n v e s t i g a t o r s f o u n d d e n s i t o m e t r i c

analyses of s ignif icant value in s tudies of coas ta l andes tua r ine dynam ics and of s ediment t ranspor t ( re fs . 6 -2 ,6-4, and 6-7 to 6-9) . W elby an d La m m i (ref . 6-9) usedcolor -encoding t echniques to in te rpre t underwa te r andshore topography . The Skylab photographs a l so proveduseful in reveal ing sedim ent in water bodies . The effectof a period of p rec ip i ta t io n on sediment d i s cha rged in to

a major lake was recognized, and the use of orbi ta lpho t og r a phs fo r measur ing re l a t ions be tween ra infa l land sedim ent load in a draina ge bas in was shown to be

possible.Szekielda (ref. 6-4) related color changes to panicu-

l a t e concent ra t ions in the s tudy of upwel l ing areas offthe coas t of northwest Africa . Gordon and N ichol s ( re f .6-8) successful ly used color encoding and micro den-s i tomet ry to ana lyze southern Chesapeake Bay wa te rcolor and c i rcu la t ion . Red- and green-band da ta w eref o u n d to be the m ost useful for map pin g wa te r types re -l a ted to t ranspa renc y , turb id i ty , and suspended-sedi -ment load. I t was f u r th e r es tabl ished that suspended

sediment could be used as a tracer of wa t e r m ove m e n tto d i s c r im ina te sma l l- s ca le m ix ing pa t t e rns and loca lt idal currents . Large-scale pat terns were shown toreflect bot tom topography indi rec t ly because th e bot-to m serves as a source of suspended mater ia l .

A near-l inear rela t ionsh ip between reflected radianc eand suspended sol ids in the concen tra t ion range of 20 to

80 p /m was found by Yarger and M cCauley ( re f . 6-7) .Pir ie and Stel ler ( ref . 6-2) foun d that varia t ions in sedi-men t concent ra tion could be observed. Figure 6-20(a) isan S190B pho togra ph of the San Francisco Bay area du r-ing a period of high sediment d i s cha rge . Microden-

s i tometer t races in the green spectra l band a re s h o w n in

figure 6-20(b) , with contour intervals ranging fromhighest reflectance and highest suspended sol ids (1) tolowest reflectance and lowest suspended sol ids (4) .Before th e Skylab overpass , an i r id ium t racer w as added






10\*

S c a l e , k m


large lakes. The mult iband analyses can therefore begrouped into photographic data reduction, e lectronicdata processing, and a combination of electronic an dphotographic data analysis .

Photographic data processing.—Hardy et al. (re f. 6-10)used S190 photographs to update an exist ing N ew YorkState land us e inventory . A key aspect of this investiga-t ion was the development of an inexpensive, systematicprocedure fo r genera ting enhanced color comp ositesfrom the filtered SI90 photographs. A color pred ict ionmodel w as developed to automate th e selection an d

generation of color composites that maximized colorcontrast between selected land use categories.Enlargements were made from the Skylab photo-

graphs, and the density range and contrast of the

enlargements of each spectral band were standardized,or normalized, so that the density of terrain featureswould correspond to the exposure range of diazo photo-graphic materials . Th e diazo photographic materials ,which are usual ly used fo r l ine-drawing reproduc t ion ,were selected because they are inexpensive to purchasean d process.

Density values obtained from each spectral band fo rkn o wn areas representing different land uses are fedinto the computerized color prediction model. Themodel relates the density values in each spectral band

for each category of land use to the spectral prop ertiesof the various diazo films. The model then produces acombinat ion of spectral-band data an d exposure data tomaximize the color contrast among the land use catego-




J N

Scale, km

F I G U R E 6-19.—Forest-stand maturi ty analys is of a woodland areain M a h o n i n g Count y , Ohio, (a ) Aircraf t photograph of a 52-hm

2

area c on ta in ing medium to smal l saw t imber . (From s tereographicana lys i s . ) (b ) S190B pho t o g ra ph ( infrared-sensi tive layer only) of

area in figure 6-19(a). ( c ) Im a g e en ha n cem en t o f S190B photograph

showing area in figures 6-19(a) a n d 6 -19( b ) . Red i n d i ca t e s m e d i umsa w t i m b e r , green indicates pole and smal l saw t imber , and blue in -dicates brush and open f ields .

ries being examined. Three land us e categories can beexamined for each composite; a set of color compositesused for land use interpretation is shown in figure 6-21.Use of the c olor-com posite data resulted in aggregate er-rors of a p p ro x i ma t e ly 12 percen t for Level I land useclassification and 25 percen t fo r Level II classification.

Electronic data processing.—A utomatic p rocessing of

Skylab photographs fo r crop classification w as evalu-ated by Colwell et al. (ref. 6-11) and Silva (ref. 6-12). Inth e land use studies , computer processing of photo-graphic density d ata that had been conv erted to digitalform by scanning w ith a microdensi tometer was used.




10S c a l e , k m

FIGURE 6-20.—Observat ions of varia t ions in sed i m en t co n cen t ra t i o n in San Francisco B ay , Cal i fo rnia , (a ) S190B c olor photograp h show ing

the deta i led surface -cur rent s t ruc ture . The spreading of the waters entering San Pablo Bay and the Pacif ic Ocean is clearly observable during

this high sediment disc harg e period (SL4-92-336). (b ) Green-band d ensi ty plo ts from the S190B color p h o t ograp h w i t h densi ty contours as indi -ca ted. Co ntour in tervals represent high (no. 1) to low (no. 4) reflectance (high to low sediment conc entra t ion ), (c) Dredge disposal p lo t over la inby suspended-sediment dist r ibut ion in San Pablo Bay . Correla t ion between sediment t ransp ort pa t tern and areas of high (10) to low (1) percen-

tage of dredged materia l can be noted.




M a re I s land

0 10

Scale, km

N

I

(b)

F I G U R E 6 - 2 0 . — C o n t i n u e d .

The four black-an d-w hi te bands of the S190A camera(green, red, a nd t wo near - inf ra red spec t ra l bands ) werescanned wi th a microd ens i tomete r us ing a spot s ize ap-p r o x i m a t e l y equ ivalen t to 0.41 hm 2 on the ground (Col -well et al., ref. 6-11). The dens i ty measurements wererecorded on m agne t ic t ape and processed u s ing pa t t e rnrecognition algori thms.

The opt imum combina t ion of spec t ra l bands wasdetermined, as were interclass divergences , f rom c om -binat io ns of crop s . A class if icat ion map based o n thet r a in ing s ta t is t ics was then generated. Fin al ly, the data

were reprocessed to p r o d u c e a map where in a "nearest

ne i ghb o r a l go r i t hm " wa s u s e d a nd a c c u r a c i e s o fclassification were computed .

The c l a s s i fi ca t ion a lgor i thm s were ap pl i ed wi thsurpr ising success to da ta f rom a set of vegetable cropsin th e Sa l inas Va l l ey , Californ ia . A na l y s i s of thesp ec t r a l densities in the four bands pe rm i t t ed c l a s s if i ca -tion to an overall accuracy of 49 percent early in thecrop cy cles and 85 perc ent la ter in the crop cycles . Thela t ter accuracy is exce l l en t cons ide r ing tha t mul t ida tein f o rmat io n was not used in the c rop class if icat ion.

Silva (ref . 6-12) a lso digi t ized S190A ph oto gra ph ic

da ta us ing both co lo r - inf ra red and b l ack-and -w hi te




(c )

Heavy concentrat ion of suspended sediment

Intermediate concen t ra t ion of suspended sediment

Minor suspended sedime nt

SA N P A B L O BA Y

Scale, km

F IGURE 6 - 2 0 . —Conc lud e d .

D A T A A N A L Y S I S T E C H N I Q U E S 279



FIGU RE 6-21.—An S190A false-color composite of the L ower Hudson V alley , New York , at a scale of 1:250 000. The color represen tations areas fo l lows: water , black; vegeta tion , red; urb an areas , blue; agricultura l areas, tan-yel low; and major highw ays, white l ines.




mu ltiba nd f ram es. The scanning spot was 25 /u ,m ind iameter , and l ines were scanned at 20- /zm interva ls . AKodak 92 filter was used to separate the red layer, aKodak 93 filter for the green layer , and a K o d a k 94 filterfor the b lue layer . The equiv alent ground size for theaper tu re used was appro xim ate ly 68 m in d iameter . The

four black-and-white f i lms of the S190A were alsodigit ized but without fil ters. A total of 256 dif ferentlevels of film density was measured, and level 255 wasset for the darkest area between f rames. The three-channel digit ized set def ined by the three dye layers ofth e color - infrared transparency maintained good spatialregistration because it was produced f rom th e samet r ansparency . The four-channel digitized set f rom th efour black-and-white f i lms of the S190A camera had tobe registered by sub jec t ing an 1100- by 1100-line blockof data to a second-order least squares fi t using 60points evenly dis tr ibuted across th e area. The registra-t ion was 40 and 70 m for the pai r of visible an d infrared

channels , respectively , but the registrat ion is w ith in twopic tu re elements (pixels) between th e visib le and in -frared bands because of differences in resolution be-tween the two types of emulsion.

Once in proper fo rmat , th e data were clustered andt raining fields for each of 12 classes were selected. Th edigit ized color - infrared data were super ior to thedigitized black-and-w hite data and had classif icat ion ac -curacies of a p p r o x i m a t e l y 80 percent . Some degradationin results w as caused by the shorel ine of a lake and thenarrow course of a r iver , which did not prov ide an ade-quate training set and would b e affected by themisregistrat ion between channels .

Th e successful appl ic at ion of automatic classificationfrom mul t iband pho tograph ic imagery i s impor tan tbecause of two character is t ics of the pho tograph ic da ta :(1 ) ease of data s torage, which permitted th e full

multispectral scene f rom th e S190A camera system tobe recorded and stored on four 5.72-cm black-an d-w hitefilm transparencies, and (2) the excel lent geometr icfidelity of the photographic imagery , which fac i l i tatedregistration and use of mul t ida te imagery .

Photographic an d electronic data processing.—Piech etal . (ref. 6-5) used microdens i tomet ry of image elementsto measure atmospher ic effec ts and subsequently toreduce and process th e mul t iband da ta in the fo rm of

target spectral reflectance values. Th e multiband ref lec-tance analyses were used to obtain th e eutrophicationindices of large lakes such as Conesus Lake, N ew Y o r k ;th e relat ive value, or ratio, of var ious ref lec tance bands

is related to eu t roph ica t ion ind ices of the lakes (fig.6-22). The reflectance of a lake is typical ly a p p r o x -imately 2 to 3 percen t , whereas the a tmosp her ic compo-nent of the signal at the Skylab spacecraf t can have areflectance of a p p r o x i m a t e l y 10 percent . A smal lchange in a tmospher ic p roper t ies f rom one sampl ing

date to another could thus be mis in terp re ted as a signifi-cant change in lake proper t ies . The accurate measure-m en t of relat ive ref lec tance values between spectralbands therefore requires accurate removal of at-mospher ic s ignal noise in both spectral bands.

The results of the invest igation dem onstrated th atimage mic rodens i tomet ry cou ld be used to specify ac -curately th e a tmospher ic c ompone n t of exposure.Figure 6-23 depicts th e relat ive values of blue- an dgreen-band lake ref lec tance as measured f rom th eSkylab spacecraf t compared to those measured f rom anaircraft und erflig ht at an altitud e of 3048 m. The aircraftmeasurement techniques h ad prev ious ly been s h o w n to

a g ree c o n s i s t en t l y w i t h g r o u n d m ea s u r em en t s o fspectral reflectance ratios. The Skylab an d ai rcraf t dataagree with in th e system measurement accuracy. The in-vestigators pointed out that increased accuracy in themeasurement of reflectance values would be obtainedby an increase in image resolution.

Subsequent reduction of the lake spectral data w asaccomplished by means of a combination of photo-graphic and electronic data processing. A black-and-whi te pho tograph ic copy , or separat ion, of each spectralband of the S190A color photograph w as modif ied ac -cording to the atmospheric effect measured fo r thatspectral band; an app ropr iate increase in image contrast

in each spectral band removed th e effects of the at-mospher ic s ignal fo r that spectral band.

May 7 ,

June 19,

Aug. 13 ,

S e p t . 9 ,

Chlorophyllconcentration, mg/m

(

1973

1973

1 9 7 3

1 9 7 3

1 1 2 3 4 5

silt

3

6,

Blue-to-green

ratio

FIGURE 6-22.—An inverse relation is shown between the blue-to-

green reflectance ratio and the surface chlorophyll concentration for

Conesus Lake, New York, du r in g 1973.




O lco tt , N .Y . Go ld P o in t,

O n tar io

2.00

, 1 . 50

.50

Trou tberg ,

N . Y .

Chub P o in t,

O n tar io

F I G U R E 6-23.—Comparison of S190A measurements of b lue- to -green ref lec tance rat io (sol id l ine) w i t h a i r c ra f t meas urement s(crosses and error bars). Eac h d iv i s ion on the hor izontal axes repre-sents 4.8 km (3 s. mi . ) .

A reversal copy w as t he n m a de of one of the cor-rected spectra l bands fo r which rela t ive reflectancevalues were des ired. An overlay of the posi t ive copy ofthe other spectra l band together with the reversal copycom pr i sed a dens i ty map p ropo r t iona l to the re fl ec tancerat io va lues of the l ake scene. Th e data were then ex -t rac ted , or d i sp l ayed , us ing a co lor -encoding device . Thecrucia l elements to the mul t iband ana lys i s , however ,were the measurement and the remova l of a tmosph er i ceffects.

Approaches and M ode l Inputs

The S kylab pho tograph ic exper im ent s e rved a s afocal po i n t fo r several invest igat ions by p r ov i d i ng am e d i um t h r ough w h i c h l ar ge areas could be s tudied bym u l t i d i s c i p l i n a r y t eams a n d t h rough which succes s fu lanalys is methods could b e verif ied and ex tended .A l t hough th e spectra l propert ies of the Sky la b photo-graphs were used in a l l these s tudies , the most impor-tant characteris t ics were large-area coverage and highspatial resolution.

S kylab photographs enab led pe r formance of an in te r -disc ipl inary s tudy of the hy d r o l ogy of prehi s tor i c fa rm-in g sys tems wi th in a large and envi ronmenta l ly d ive rsearea of central A rizon a (G um erm an et al. , ref. 6-13; fig.6-24). Hydrologists, geologists, biologists, and archeolo-

g i st s eva lua ted the adap ta t ion of prehi s tor i c hum ans tothe semiarid desert of centra l Ar izo na, and the ir crea-tion of l a nd m a na ge m e n t and wa ter control sys tems.Such an analysis required data over thousands of square

ki lomete rs and an und ers tandin g of the num erou sv ar ia t io n s in env i ron me nt over th i s reg ion . Coverage of

such a large region us ing o n l y ground ac t iv i t i e s is im-poss ible . Data from Skylab or h igh - a l t i tude - a i rc ra f t

sys tems provide th e archeologis t w i t h a s igni f i cantreg ional perspec t ive fo r un ders tand ing sur face geology ,hydro l ogy , a n d vege ta t ion p a t t e rns a n d enable formula-

tion o f specif ic quest ions and r e l a t ions h i p s a m ong th e

envi ro nm ent , preh i s tor i c s e t tl ements , an d subs is t ence

systems.The s tudy covered an a rea ex tending from t he Lower

Sonoran Life Z one j u s t no r t h o f P h o e n i x to the U p p e rSonoran Life Zone jus t south of Prescot t , including a

bio logical t rans i t ion zone be tween th e desert floor andth e p l a t e a u . E c o l o g i c a l l y s i g n i f i c a n t s u b a r e a s , o r

dra inage basins , were selected for s tudy on the bas is ofbasin area, stream length and order , s lopes , bedrocktype , and ra infa l l di s t r ibut ion . Es t ima t ion of ava i l ab lewa te r w as es tabl ished from t hese p a ramete rs and fromvege ta tion comm uni t i es . W i th th i s informat ion , i t wasposs ible to predict with some accuracy the bas ins mos tl ike ly to have prehi s tor i c wa te r management sys tems .D el ineat ion w as based p r i m a r i l y on the topography andgeometric characteris t ics of the drainage bas ins . Th edra inage i n f o r m a t i on f r om th e S k y l a b pho t og r a phs ,together with s lope a nd l andform da ta f rom high-r e so l u t ion U -2 a ircraf t imag ery , enab led a rcheologis t s todiscern potent ia l areas of prehi s tor i c uti l izat ion .

W i t h i n th e basins most sui ted fo r agr i cu l tura l pur -poses, a series of exp lo i ta t io n model s for one s tudy a rea(fig. 6-25) w as developed by using th e t opog r a phy ,s lope, a n d dra inage pa t t e rns in te rpre ted f rom Sky la b

and U-2 pho t og r a phs . A decis ion model developed byPlogg and Garret t ( ref . 6-14) was used to evaluate thea l t e rna t ive exp loi ta t io n schemes for the ent i r e area . Th emode l was in fo rma l ly tested us ing the rem ote-sensinginterpreta t ions together with s ta t is t ica l data from thet r ad i t io n a l sources as inputs . The resul ts provided thearcheologis ts with a fairly comprehens ive unders tand-ing of the cul tura l and economic pa t t e rns for a large p or-t ion of the centra l Arizona area .

FIG U RE 6 -2 4 .—Index map of Ar izona , s howing th e locat ion of theBasin and Ran ge, Trans i tion Zone, and Mesa Cany on phy s iograph iccomplexes . —>•

2 8 2 S K Y L A B E R E P I N V E S TI G A T IO N S S U M M A R Y



T r a n s i t i o n Z o n e c o m p l e x

B a s i n a n d R a n g e

c o m p l e x




A g u a F r i a R i v e r

"M esa Canyon

' complex

Trans i t ion ZoneBasin and R a n g e || complex

complex

(a) A

Agua F r ia R ive r

' M e s a Canyon

' complex

T ra n s i t i o n ZoneBasin an d R a n g e J | complex

complex

a

Agua F r ia

'Mesa Canyon

B ' complex

T rans i t ion ZoneBas in and R ang e ) | comp lex

complex

(e

M esa Canyon

" complex

A g u a F r i a R i v e r

Basin an d R a n g e

complex

(d)

Agua F r ia R ive r

"M esa Canyon

complex

Transit ion ZoneBasin and R ang e) ] complex

complex.

(•I

Agua F r ia R ive r

M esa Canyon

complex

Transit ion ZoneBasin and R a n g e || _ complex

complex

Ifl

F I G U R E 6-25.—Alternative models fo r exploitation of the central Arizona area by prehis tor ic c ivi l izat ions . The organizational schemes define

a l t e rna t ives fo r social an d na tura l ut i l i zat ion of the are a d ur i ng th e per iod 1000 to 1400 A.D. The models (not to scale) indicate consideration ofe nv i ronm e nt a l parameters such as re lat ive areal posi t ion, e levat ion, slope, surface m ater ials , an d w at e r ava i l ab i l i t y , (a ) Model 1. (b) Model 2.(c ) Model 3 . (d) Model 4. (e) Model 5. (f) M o d e l 6.




An extens ion o f t he p rec is ion o f mul t i s tage sam pl ing

of t i m b e r v o l u m e to a Sky l ab da t a base was ac-comp l i shed by L ang l ey and V an Roessel ( r e f . 6 -15). Inmul t i s t age sampl ing , smal l - sca l e pho tographs are usedto del ineate regions of homogeneous charac t e r i s t i c s ,large-scale pho togra ph s are used to specify f ie ld plots of

th e s a m p l e classes fo r ground measurement s , and sub-sequen t g round measurement s of yie ld or v o l u m e areused to develop the field p l o t s of the sample c lasses.Th e invest igators developed a resect ion technique fo rt he Sky l a b pho tograph s t ha t pe rm i t t ed accura t e l oca t ionof s a m p l e - u n i t b o u n d a r i e s on the p h o t o g r a p h s . Th e sub-sequen t ana lysis of the inv en tor y precision resul ted in

th e d e t e r m i n a t i o n of i nc reased econom y and eff ic iencya t t r ibu tab le to the space pho tographs . Th e precision ofth e vo l ume e s t imate cou l d b e fu r the r improved t h rough

t he use of mul t i da t e pho tographs ; howeve r , L ang l eyemphas i zed t ha t an increase in resolut ion to the p o i n t a tw h i c h i nd iv idua l t ree s can be d i sc r imina t ed w oul d p ro -

vide the most s ignif icant increase in t imber-volume ac-curacy .

THE S192 M U L T I S PE C T R A L S C A N N E R

A l t h o u g h p h o t o g r a p h i c s y s t e m s p r o v i d e b e t t e rspatia l resolut ion because of s im pler const ruc t ion and

th e avai labi l i ty of good -qua l i ty lenses and modern h igh -resolut ion f i lms, op t i ca l -mechan i ca l imag ing sensors

have four advantages re lat ive to the usua l pho tograph i csys t em: (1) the sensors ope ra t e in spect ral regions nota v a i l a b l e to p h o t o g r a p h i c s y s t e m s ( i. e. , g e n e r a l l ybeyond 1 M m ) , (2 ) the po s i t ion and wid th o f e achspect ral band can be specif ied and con t ro l l ed , (3) thesensors ope ra t e s imul t aneous l y in several spectralbands whe re in each p ixe l is in bo th pos i t i on and t imeregist rat ion across all spect ral bands, and (4) the dataa re bet ter cal ibrated. A s e x p l a i n e d p r e v i o u s l y , th eS190A camera system provided registered mul t ibandimage ry wi th co l o r and co l o r - in f ra red f i l m , and wasrad iome t r i ca l l y ca l ib ra t ed . Howeve r , th e spect ral bandsove r l apped to a degree, and the i r locat ion and w i d t hcould not be a l te red . Wh en th e mu l t i chann e l e l e c t ri ca l

analogs of the scene are recorded on CCT's, a w i d erange of signal -processing techniques becomes avai l a -

b le . Modern, high-speed computers can process th elarge volume of data generated by sate l l i te sensors.

Thi r t een bands of i n fo rmat ion be tween 0.4 and 13nm recorded in the SI92 differed from th e four -band

Landsat systems that operate be tween 0.5 and 1 / x m . A

cons ide rab le am ount o f t heoret ica l work invo l v ings ta t is t ical dec i s ion t heory h as been a p p l i e d to the proc -essing of a i r c r a f t mul t i spec t r a l scanne r da t a wi th vary -in g degrees of success. The Skylab SI92 sensor w asdesigned to a p p l y these soph i s t i ca t ed schemes to spaceda t a , i n which bo th r e so l u t ion and a tmosphe r i c e f fec t s

were d i f fe ren t f rom those encoun te red a t a i r c raf ta l t i tu d es . Th e ques t ion conce rn ing th e o p t i m u m b a n d sas seen from space for specif ic disc ipl ines needed to beaddressed.

Sky la b i nves t iga to r s used SI92 da t a as c o m p o s i t e im -ages a n d c o m p u t e r - c o m p a t i b l e t a p e s t o d e r i v ep a r a m e t e r s of interest fo r agr icu l ture , wa ter resources,oceanography , l and use , and geological and hydro l og i ca lproblems. A few invest igators de termined the effects ofa t m o s p h e r i c a t t e n u a t i o n and scat ter ing on the un ique -

ness of signatures fo r differe nt c lasses of objects and onth e problems of signature extension.

Th e un ique advan tages of the S I 9 2 M u l t is p e c t r a l

Scanner form th e basis fo r discussion of image analysist e chn iques . In some cases, invest igators appl ied o ldtechniques to new problems, whereas in o the r s , newmethods were developed fo r using th e m u l t i s p e c t r a ls c a n n e r d a t a . T h e d a t a a n a l y s i s t e c h n i q u e s a r eorganized into four groups.

1. Single-spect ral -band techniques— The invest iga-to r used t he i n fo rma t ion in a s ing l e spec t ra l band .

2. Two-spec t ra l -band t e chn iques—In some s tud i e s ,th e invest igator required the use of o n l y tw o spec t ra l

bands.3 . Mul t i p l e - spec t ra l -band t e chn iques—In these in -

vest igations, m ul t ip le spect ral bands, three or more , a reused e i ther to generate fal se -color imagery or to per-form mu l t i spec t r a l pa t t e rn r e cogn it i on .

4 . Imagery use in Earth resource models—For ex-ampl e , a meteorological model m ay incorporate surfacet e m p e r a t u r e a s a k e y p a r a m e t e r i n m o d e l i n g

phenomena such as winds , c l ouds , or ra infa l l . The datafrom th e scanner can be used to i npu t su r face t em-

peratures into th e mode l and t hus infer th e meteorologi-cal cond i t i ons p red i c t ed by the model.

Single-Spectral-Band Techniques

Th e r ad iome t r i c p rope r t ie s of a single spectral band

can b e advantageous in some appl icat ions research. Th egeneral approach for use of s ingle -band radiometr ic datawas to develop em pir ica l corre lat ions be tween th er ad iome t r i c i n t ens i t y and a spec i f ic p rope r ty of the sur-




N =

o - = ± 4 . 0 0 , iW / ( c m2-s r )

Class i n te rva l = 0.5

_1 2 3 4 5 6 7 8 9

Radiance, ^ i W / ( c m2-s r )

10 11 12

FIGURE 6-26.—A f r equ en c y dist ribut ion (normal ized to u n i t y ) of

th e radiance in band 8 . The primary peak at the left represents clearocean; t he b ro a d pea k cen t e red a t 7 ^ i \V/ (cm 2 -sr) i s due to cloudsa n d l a n d .

around the low radiances represents water , whereas th e

cluster at the high end represents clouds and land. Pre-vious work ( ref . 6-16) establ ished the Gaussian d ist r ibu-

tion of the radiance A ' reflectance from th e ocean;therefore, by a suitable fi t of the data for the waterref lect ion , a radiance range of th r ee s t andard dev ia t ions

around the mean rad i ance N = 0.5 ^ i W / ( c m 2 « s r )shou l d i nc l ude all c l oud- f ree p ixe l s .

The range is then spread over the avai lable dynamicrange of the display by the condi t ions ( for a negat ive

image)

X = 0 for N > N + ka

. M [ ( N -ka)-N]

2k a

for (N - ka) < N <

X = M for N < N < ka

H - k o )

(6-1)

face. By the careful choice of spectral band, a greatv ar ie ty of surface condi t ions can be mapped, i n c l u d i n g

soil salinity, land use patterns, and lake outlines. In ad-

di t ion to radiometr ic intensi ty data, the single -spect ral -band imagery contains informat ion on the spat ial dis-

t r ibut ion of intensi t ies . Fourier t ransformat ion can beused to analyze the spat ial f requencies in single -bandimage data and to corre late them with geologic or hy-

drologic features of the surface. In the fol lowingparagraphs , spec i f i c exampl e s of these t e chn iques aresummar i zed .

M a u l et al . (ref. 6-16) used S192 imagery to studycloud features over th e At l an t i c Ocean between Flor idaand Cuba . O ne ana l y t i ca l t e chn ique used was the auto-matic detection of clouds to specify free areas fo rfur ther sea-surface temperature or ocean color measure-

ments. Band 8 (0.98 to 1.08 Aim) w as chosen because ofit s h igh a tmosphe r i c t r ansmiss iv i t y and h igh wate r a b -sorpt ion. Figure 6-26 shows the f requency dist r ibut ionfo r the wa ter and c loud signals in band 8 . The c luster

whe re M i s t he ma xim um val ue a l lowed by the d i sp l ay ,N is the m e a n radianc e of the c loud -free data, o- i s thestandard dev ia t ion , and k is an arbitrary constant. B yse t t ing k = 2 , 95 perc ent of the c loud-free data wo uld

be recorded over the full range of the disp lay . D etectionof anomal ies on the ocean surface would b e i m p r o v e dby t h i s me thod o f enhancement .

The prob l em of area measurement using digi tal

values and f ini te spatial resolution leads to errors forthose p ixe l s con ta in ing par t s of two classes. Gilmer andW ork (ref. 6-17) faced this prob lem in at t empt ing tomeasure lakes and pond areas and the i r changes.Usual l y , a ll wate r areas are underest imated. Using th e1.55- to 1.15-fim band of the S192, pixe ls wi thin th eb o u n d a r y of each lake in their test si te were counted. Interms of percentages, higher errors were more frequentfo r smaller ponds and for those with i r regular shapes.Because of the conical scan, th e actual errors varied de-p e n d i n g on the size and shape of the conical scan direc-tion.

2 8 6 S K Y L A B E R E P IN V E S T I G A T I O N S S U M M A R Y



Techniques Invo l v ing Tw o Spectral Bands

T h e i n t e n s i t y o f r a d i a t i o n r e c e i v e d b y t h emult ispect ral scanner f rom a given e lement of theEarth's surface is inf luenced pr imari ly by the reflec-tance of the surface and the Sun angle . However , other

factors such as the angle or s lope of the surface and theam ount o f a tmos phe r i c haze o r c i r rus c l ouds ove r t hesurface i n f l uence th e in t ens i t y of rece ived radiat ion. Toa first a p p r o x i m a t i o n , th e effects of i l l umina t ion , ang l e,haze , and c louds can be suppressed by divid ing the in-tensi ty in one b a n d by the in t ens i t y of a d i f fe ren t

spect ral band. Th e b and rat io i s large ly a funct io n of the

d i f f e r e n c e of surface r e f l e c t i v i t y at the two

wavelengths. Several invest igators used this generaltechnique in the i r invest igat ions.

V i n c e n t et al. (ref. 6-18) used S192 an d S191 data tos t u d y the feasib i l i ty of using rat ios of spect ral -band sig-nals to map i ron compounds in the exposed surfaces of

rocks and soi l and to di fferen t iate sil icate rock types. Ageneral invest igat ion of l aboratory spect ra had been

T A B L E 6-1.—Ranking of Simulated SI 92

Bands fo r Producing A utom at ic R ecognit ionMaps of Rock, Mineral, and Soil Classes*

conducted ( ref . 6-19) by which the best bands for dis-c r imina t ing rock , m ine ra l , and so il classes were de ter -min ed. Tables 6-1 and 6- II show the ra nking s of thes imul a t ed SI92 bands fo r single -band and t w o - b a n d -ratio processing, respect ive ly . The value of ope ra t ingsa t e l l i t e sensors in n a r r o w bands such a s t h o s e

e m p l o y e d in E R E P is s h o w n by the order ings. Usingl abo ra to ry and f ie ld spec t ra , op t imum spec t ra l r a t i oswere de t e rmined fo r mapp ing iron compounds . Com-parison of the resul ts of S190B ph oto inter pre tat io n ands ingle- level s l i c ing me thod s w as a l so p e r fo rmed . N ot a l lop t ima l r a t ios cou l d be fo rm ed w i th t he da t a se t ava i l -

able, b u t those bands in the red , near i n f ra red , an d the r -m al infrared proved most useful . After suitable conver-sion and noise-reduct ion steps, three rat ios were formedf rom t he da t a .

Band 8

Band 7

Band 11

Band 7

Band 12

Ba nd 11 1.55 to 1.73

0.93 to 1.05

0.77 to 0.89

1.55 to 1.730.77 to 0.89

2.10 to 2.34

R a n k Band

Number Wavelength, \im

1

:3456

7

89

10

1112

12

82

1 15

4

79

1 0631

2.10 to 2.34

0.93 to 1.050.45 to 0.50

1.55 to 1.73

0.60 to 0.65

0.54 to 0.60

0.77 to 0.89

1.03 to 1.19

1.15 to 1.28

0.65 to 0.73

0.50 to 0.55

0.42 to 0.45

Based on discr iminan t ana lys i s of 211 laboratory spectra.

The ratios R i/ 7 and R n / 1 were chosen to different iateferr ic and ferrous mater ial s . For prope r impl ementa t ionof the technique , the signal f rom atmospheric path ra-diance must be subtracted from the scene elements by

u s i n g t h e d a r k e s t o b j e c t s u b t r a c t i o n m e t h o d .Specif ical ly , an analysis of the darkest objects in thescene is made , th e mean va l ue is calculated, and t h a tvalue is subtracted f rom al l p ixe ls . After subtract ion,th e range of the rat io is adjusted fo r m a x i m u m c o n t r a s t .For the test si te shown in figure 6-27(a) , th e rat io image/? 8/ 7 w as const ructed and is shown in figure 6-27(b) .This rat io proved best for separa t ing ferr ic , ferrous, and

nonferrous classes of materials. The color codes defineth e range ( low to h i g h ) of rat io values. The basaltic andacidic rocks are imaged in the test site as blue ( lowra t io ) , wh ich i s i nd i ca t ive o f f er rous com pounds . The




T A B L E d-ll.—Tw elve Best Band R atios for ProducingA utoma t i c Recognition Maps of Rock , Mineral,

an d Soil Classes From Simulated Si 92Scanner Dataa

R a n k

'

:

•

4

;

•

-

-

9

:

1 1

12

Ratio

/., (0.77 to 0.89 Mm)Ryi

£,(0.60 to 0.65 Mm )

L} (0.50 to 0.55 M m )3/2

L2 (0.45 to 0.50 Mm)

L 8 (0.93 to 1.05 M m)8/4

£4 (0.54 to 0.60 M m )

D £ 1 0 ( 1 .1 5 t o l . 2 8 M m )10/9

L 9 ( 1 . 0 3 t o l . l 9 M m )

I12 (2.10 to 2.34 Mm)1 2 / 1 1

Z . n ( 1 . 5 5 t o l . 7 3 M m )

£7 (0.77 to 0.89 M m )7/3

£3 (0.50 to 0.55 Mm )

£4 (0.54 to 0.60 M m )4/2

£2 (0.45 to 0.50 M m )

£4 (0.54 to 0.60 M m )4/3

£3 (0.50 to 0.55 Mm )

£7 (0.77 to 0.89 Mm)7/ 2 L 2 (0.45 to 0.50 M m )

£7 (0.77 to 0.89 M m )7/4

£4 (0.54 to 0.60 / tm)

£8 (0.93 to 1.05 M m )8/3

£3 (0.50 to 0.55 M m )

Ls (0.93 to 1.05 M m )

L- , (0.77 to 0.89 M m )

aBased on di scr iminan t anal ys i s of 21 1 laborato ry L spectra.

high-rat io values (reds and oranges) relate to the ferric

sed iment s t ha t f lank the slopes of the h igh l ands . As theconcen t ra t i on o f ferric i ron decreases in the surf ic ialdeposits of the valley floors, the color shifts to yellow

and green, an ind icat io n of interm ediate v alues ( fig .6 -27(b ) ) .

Th e ra t io process produced images that were muchless inf luenced by v a r i a t i o n s in i l l u m i n a t i o n a nd te r ra in

s h a d o w s , a prob l em tha t r educed th e effect iveness ofs ingle-band enha ncem ent t e chn iques . In one case , faul t

locat ion re lated to the abrup tness of a color- boun dary

change was enhanced .The bands found useful in this invest igat ion should

he l p t o de f ine t he op t imum p l acement o f bands fo rfu ture mult ispect ral scanner sensors. C u r r e n t L a n d s a tb a n d s a re excessive ly broad; Landsat band 7 i n t eg ra t e sboth ba nds used in the /? g/ 7 rat io .

Yarger an d McCaul ey ( r e f . 6 -7 ) found band ra t i ost h a t gave best results for a s t a t i s ti ca l co r re l a t i on w i th in -

o rg an ic suspended sol ids in three Kansas reservoirs .The CCT's for the S192 data were used to select th eprope r pixe ls wi th in each of the reservoir images for the

n ine bands ana l yzed . T h e pixels were averaged, and t hesignal level was converted to radiance levels .

Th e most effect ive bands were rat ioed, and thevalues were plotted as a func t ion of suspended solids(fig. 6-28). T h e r ed /g reen ra t i o imp roved th e cor re l a t i onw i t h suspended l oad when comp ared to i n d i v i d u a l - b a n d

performance . The rat io of infrared/green also exhibi teda good l inear correlation with suspended load. Agree-m e n t with L andsa t da t a i s a l so shown.

Th e effectiveness of the ra t io me thod to d i s c r i m i n a t ebetween ice crystals and water drople t c louds wasstudied by Curran et al. (ref. 6-20) and Pitts et al. (ref.6-21). These au thors found t ha t t he i n f ra red band cen -tered at 1.65 /urn rat ioed w i th a l ower wave l eng th bandh as potent ial fo r separa t ing ic e clouds, l iqu id wate rdrople t c louds, and snowfie lds.

Techniques Invo l v ing M ul t i p le Spectral Bands

Three or more spect ral bands can be c o m b i n e d top r o d u c e a false-color image. In t h i s way , th e spect ralbands invisib le to the hu ma n eye can be rendered visi -b le and used fo r in t e rp re t a t i on of the scene. Th e genera-t ion of false-color images and t he i r ana l ys i s was a m a j o r

use of the Skylab mul t i spect ral scanner data . A secondme thod fo r ana l ys i s of mult iple -spect ral -band data in -volved the use of pat tern recogni t ion techniques anddig i ta l compute r s . Many me thods fo r compute r -a idedanal ys i s o f m u l t i s p e c t r a l i m a g e data have been

deve l oped dur ing th e past decade, and these m e t h o d swere appl ied to the Skylab mul t i spect ral scanner imag-

288 S K Y L A B E R E P I N V E ST IG A T IO N S S U M M A R Y



ery wi th general ly successful resul ts . Examples of the

ap p l ica t io n of f a l se -co l o r image ry and compute r -a idedanal ys i s o f mul t i spec t r a l image da t a a re summa r i zed inp a r a g r a p h s w h i c h fo l low.

In processing S192 data, th e a p p r o a c h t a k e n by Col-wel l et al . ( ref . 6-11) was to de te rmin e the best com bina-

t ion of four channe l s t ha t cou l d be used to effect ive lyclassify an area . Th i s approach was selected t o m i n i -m i z e p r o c e s s i n g - t i m e costs w i t h o u t s a c r i f i c i n g

classification accuracy .

Each of the 22 sc i en t i f i c da t a ou tp u t (SDO ) ch anne l s( app . A , t ab l e A - I ) o f S192 scanne r t ape was inspec t edon a t e l ev i s ion moni to r to screen out unusab l e da t a ont he bas i s o f no i se l eve l o r sa tu ra t ion . Three chan ne l swere used in a color mo ni t or to faci l i ta te the selection of

t r a i n i n g fields. Coordinates of se lected f ie lds wered e t e r m i n e d f r o m a g r i d n e t w o r k d i s p l a y e ds i m u l t a n e o u s l y w i t h th e tape data. After se lect ion oft r a i n i n g se ts , convent ional s tat i s t ical analysis of the

da t a w as pe r fo rmed .The data w ere rec lassi fied u sing th e nearest ne ighbor

a l gor i t hm as we l l as a t h re sho l d a l gor i t hm by which apo int was rec lassif ied only i f a s tated pro ba bi l i ty of cor-r ec t c l ass i f i ca t ion was a t t a ined . In a p re l iminary test,

SD O channe l s 2, 3, 8, and 12 were de t e rmined as neces-sary for c lassi f icat ion ; for anoth er test, cha nnels 2 , 3 , 8 ,

9, 10, and 12 were found to produce usable resul ts .L a t e r , for an e x te n d e d a r ea , n i n e c h a n n e l s ( 2 , 6 , 8 , 9 , 1 0 ,

1 2 , 1 8 , 2 0 , and 21) were used to de te rmine th e best com-b i n a t i o n of four channels . Classi f icat ion tests m a d eusing cha nnels 8 , 18, 20, and 21 resulted in high ac-cu racy , e spec i a l ly w hen th e nearest ne ighbor algori thm

w as used. This resul t w as expected because th e nearestneighbor algori thm reclassi f ies each point as one of adefined set of crop classes, whereas the second

classi f icat ion technique using th e threshold algori thm

reclassifies a p o i n t as one of the defined set or defines ita s unc l ass if i ed . Fur the r s tud i e s wi th E R EP da t a y i e lded

results based on a na lysi s of al l 22 cha nnels for an area inn o r t h e r n Fresno, Ca l i fo rn i a , con ta in ing a var i e ty o fc rop types i n d i f f e ren t states of matu ra t ion .

The best c o m b i n a t i o n of four spect ral bands fo r dis-cr im inat in g crop subclasses w as de te rmined to be 4 , 7 , 9 ,

and 11 , w i t h b a n d 10 or b a n d 8 serving as a sui tablesubst i tute . However , th e c o m p l e x i t y of the agricul tural

scene investigated resulted in an ove ra l l pe r fo rmanceaccuracy of 57 percent . After rec lassi f icat ion into 13

classes for 22 subclasses, the performa nce accu racy in-creased to greater than 66 pe rcen t .

T h e s t u d ie s s h o w e d t h a t , d e p e n d i n g o n t h eagr icu l tural e n v i r o n m e n t , season, and s t a t e o f m atu r i t y ,t h e o p t i m u m c o m b i n a t i o n o f b a n d s wil l vary . For al imi ted i n v e n t o r y of one or two crops, s ing l e bands

m i g h t be adequate . The imp or t an ce o f t he near - in f ra redregion was pa r t i cu l a r ly demons t ra t ed .

Silva ( ref. 6-12) a na lyze d S192 data for an Ind ian atest s i te by c luster ing of s igna l l eve l s wh ich showed tha tsepara t ion of 13 subclasses w as possib le . A separab i l i t y

measure w as used to find the best 4 of the 12 b a n d sevalua ted; nam ely , bands 3 , 7 , 8 , and 11. The four

Sky la b bands gave bet ter resul ts than four bands used tos imul a t e L a ndsa t b ands , bu t t h i s r e su l t cou l d be due tobo th i n fo rm at ion and no i se d i f fe rences .

Ove ra l l , t he pe r fo rmance o f t he S I92 op t imum fourbands w as bet ter than th e resul ts obtained w i t h digitized

pho tographs and was essent ial ly equal to resul ts ob-

t a ined f rom ana l ys i s of L andsa t da t a t aken t he daybefore th e S k y l a b pass, despi te th e fact that th e Sky l abdata were noisier . Figure 2-11 in sect ion 2 (Land Useand C a r t o g r a p h y ) s h o w s th e color-coded resul ts fo rn ine l and use classes.

Th e classi f icat ion procedure used th e pat tern recog-n i t i on a l gor i t hms t ha t have been implemented in a sof t -ware package ca l l ed L A RS YS ( re f . 6 -22) . Tra in ing f i e ldsfo r 12 classes, r ep re sen t ing ap pro xim ate l y 0 .3 pe rcen tof the s tudy area , we re sca t t e red t h roughou t th e s t u d yarea.

Th e training f ie lds were evaluated using a cluster ingrou t ine to de te rmine whe the r fu r the r d iv i s ion of the 12

classes w as necessary to ensure that each of the resul t -in g spect ral classes represented a un imodal d i s t r i bu t ion .Assuming t ha t th e spect ral data of the s a m p l e s fo r each

spectral class h ad norm al (Gauss ian ) d i s t r i bu t ion , th e^-dim ensional m ean vector a nd t he N b y TVcovariance

mat r ix of the mul t i spec t r a l da t a sets were computed fo reach class, w h e r e W represents th e n u m b e r of channe l sof spect ral informat ion in each data set . Th e mean vec-tors and covar i ance mat r i ce s we re used in the ac tua l

c lassi f icat ion rout ine , which incorporates th e m a x -imum- l ike l i hood decision rule (ref. 6-23) with the apr ior i pro bab i l i ty of occurrence for each class beingequal .

A modif ied divergence rule w as used to select th ebest 4 of the 12 bands in the Sky lab SI92 data se t eva l u -




«*1

C o p p e rM ountai

S c a l e , k m

FIGURE 6-27.—The Pisgah Crater test site in Ca l i fo rn i a , (a ) S190B photograph (SL4-92-351). (b ) Color-coded R ir ra t io image (January 26 ,1974).

ated. Divergence is used because it is a measure of sepa-

rabi l i ty between two densi ty funct ions that representtwo classes of objects. This modified divergence (calledtransform ed divergenc e) was extended to a mu l t iclasscase to choose th e best four b a nds in two separate ways .

Firs t , th e average of the t rans formed d ivergence for al l

possib le c la ss pa i r s was max imized ; then , the m inim umtrans formed d ivergence of al l possible class pairs w asm a x i m i z e d . I t canno t be show n, how ever , t ha t e i the r ofthese methods is o p t i m a l . Four bands we re selected for




Low

rat io XF I G U R E 6 -2 7 .—C onc luded .

Hi g h Rat io

rat io uncalculated

th e class if icat ion to r educ e c om pu t e r costs and to deter-m i ne whe t he r th e bands selected included any spectra l

bands not ava i l ab le in the other da ta sets.

T h e produc t s ob ta ined in the s tudy inc lude th et rans formed divergence measures for the sepa rab i l i ty of

each pa i r of classes in each data set , th e class if icat ionm a ps , and the class if icat ion perform anc e resul ts . Th e

classification performance resu l t s were ob ta ined b yselect ing s ix tes t areas scat tered throughout the s tudyarea represent ing th e classes under considerat ion.




1.00

•

•

8 . 5 0

:

•

.2 0

.1 0 -

, L inea r fit (±1 standard deviationl

to Landsat bands 5/ 4 (red/green)

f it (±1 standard deviation)

to Landsat bands 6 /4

(infrared/green)

O S192 (red/green)

D S190A ( red /g reen)

A S192 ( inf rared/green)

0 S190A ( inf rared/green)

10 20 30 40 50

Suspended solids, p/m

• n

F I G U R E 6 -2 8 .—R adianc e ratios as a func t i on of suspended solids.The data were taken over three southeastern Kansas reservoirs dur-

ing th e period July to September 1973.

motion and Ear th ro ta t ion dur ing th e acquisi t ion t imeof a given f rame. In the process, 1240 original samplesalong a scan l ine were reduced to 1056 samples/l ine.

Once in this form, images can be easily made to fillth e dyna mic r ange of the display m ed i u m by m ea n s ofcontrast enhan cem ent. Pairs of images havin g inte n-

sities 7, and I2 were compared by a rat io a l gor i t hm of theform

(6-2)

where I0 is the outp ut image inten si ty and the tw o con-stants a and b are chosen to maximize contrast and maychange fo r dif ferent scenes. This tech niqu e proveduseful fo r t empora l and spec t r a l compar i sons .

O ne classification algorithm that w as used is calledstepwise l i near -d i sc r iminan t analysis (ref . 6-24). It con-sists of f inding a t r ansform tha t min imizes th e rat io ofth e difference between group-multivariate means to thegroup-mul t iva r i a te var iances .

A second tech nique used was a hyb r id app roach.First, fo r each spectral band , the means A'and th e stand-ar d dev ia t ions 6- for each category ar e c o m p u t ed . Th epaired categories are compared fo r each band and deter -mined to be separable if they satisfy the relat ion

Photographs were projec ted onto th e classif icat ion m apof these test areas, and a p o i n t - b y - p o i n t c h ec k of theclassification w as done. The points f rom all six testareas were combined to obtain performance resul ts fo reach c lass and for the overal l c lassificat ion perform ancerepresented by the total nu mb er of poi nts c lassif ied cor-rectly divided by the total number of test-area points.

In the proce ssing of S192 data by Goetz et al. (ref.6-24), scan lines w ere added or deleted where necessaryto correct fo r scale. Unusual lines were modified by in-serting an average of neighbor ing l ines and therebyreducing th e noise level. The high-data-rate channels (1to 16) were merged into a single band equivalent to thelow-data-ra te channels (17 to 22). Geom etr ical rec t if ica-

t ion was perform ed as a pre l im ina ry s tep to comp ensatefor a 5.5° cone angle and for the 110° scan arc motion ofthe sensors. A correction was also made for spacecraft

> 1 ( 6-3 )

where C is a constant . The hybr id c lassif icat ion com-bines t w o e x i s t i n g c l a s s i f ic a t i o n s c h e m e s , t h eparal le lepiped a lgor i thm and the B a y es ia n m a x i m u m -l ikel ihood funct ion.

The para l l e lep iped a lgor i thm approximates a hy-perel l ipsoid tha t i s def ined by comput ing means ,var iances, and covar iances based on the assumption ofa Gaussian distribution for the signal va riations fo r eachcategory in the selec ted wavelength bands. Decision

bound ar ies , related to the num ber of s tand ard devia-tions about th e mean, can be defined by the computeroperator . Each band is considered a vector c omp onent;




i .e . , the set of spectral bands for a given category is avec to r in mul t i d imens iona l space . Idea l l y , all p ix e l vec-tors for a given category wil l cluster about a well -

def ined m e a n w i t h smal l var i ances t ha t fall w i t h i n a

nar row el l ipsoid.M a x i m u m - l i k e l i h o o d processing depends on the

knowl edge of a prior i probabi l i t ies . The data set can bein tegrated to def ine the p robab i l i t ies , but th e l ike l iho odusual ly i s de f ined by t he mu l t i var i a t e Gauss i an p rob -

abi l i ty dens i ty func t ion .Goetz et al . (ref. 6-24) used an in t e rac t ive unsupe r -

v i sed c l us t e r ing a l gor i t hm . The in t e rac t ive te chn ique in -co rpora t e s a se l f -g roup ing me thod based on the bestpar t i t ioning of N objects in to g groups by m a x i m i z i n gth e variat ions be tween groups and m i n i m i z i n g th evar i a t i ons w i t h i n groups. Several cri ter ia t hen can beconsidered in se lect ing th e best group ing . Th e methods

u s in g t he var ious c r i t e r i a a re t ime consuming and re -qu i re l a rge -compute r capab i l i t ie s . Some rand om sam-

p l in g of the scene to give th e in i t ia l cluster ing is per-fo rmed to m a k e th e t e chn ique more p rac t i ca l .Other invest igators , such as Sat t inger et al . (ref.

6-25) , in studying techniques for land-cover inventor ies ,deleted t he two doub l y sampl ed t he rmal channe l s .Fi rst , noise levels and dyn am ic ranges we re assessed bym a k i n g a histogram of the data values in each spect ral

b a n d . Some differences were noted in the h i s togramsfo r even- and odd-numbered SDO's. B y t h i s process,

on l y th e bet ter data channels were used.A n op t imum band se l ec t ion p rogram w as i n v o k e d ,

and the best s ix bands we re de t e rmined . In order ofpreference , these were 0.78 to 0.88, 1.55 to 1.75, 0.98 to1.08,0.68 to 0.76,0.52 to 0.56, and 0.62 to 0.67 pm. I t ap-peared t ha t th e choice w as dependen t on the signal - to-noise rat io a nd on spect ral contrast .

Seasonal compar i sons us ing March to June da t a we reconsidered best . By means of supervised c lassi f icat iont echn iques , th e best s ingle -band de l ineat ion (1 .55 to1.75 /*m) w as used as a base on to which 2 .6 -km 2 gridsect ions were t ransferred. Th e section l ines h ad been

traced from a 1:120 000-scale co l o r - in f ra red t r anspa ren -cy spa t ial ly registered to the digital map of S192 data bya t ransfer scope. This gr id enabled bet ter locat ionreference for the t raining sets when ana l yz ing t he S192

dig i ta l data. Thir ty-f ive separate sets were designated toencompass the wide variabi l i ty of the categories of in-terest. E n l a r g e m e n t s ( 8 x ) o f S190B photographsproved va l uab l e in se lect ing boundaries of t r a in ing sets

and j u d g i n g th e homogene i ty of f ie lds.

M e a n s and var i ances fo r each t r a in ing se t were com-p u t e d w i t h a l l bou nda ry p ixe l s exc l uded f rom ca l cu l a -

t ions. A test for s igna ture stat i s t ical uniqueness wasm a d e b y c o m p u t i n g th e proba b i l i ty of m i sc l ass i fi ca t ionfo r all possib le pai rs of s igna tu re s . Each pa i rw i se p rob -abi l i ty of misclassi f icat ion provides a measure o f the

separabi l i ty be tween two m ul t i d imen s iona l s t a t i s ti ca ld is t r ibu t io n s . It represents an average of the prob -abil i t ies t ha t sampl e s f rom d i s t r i bu t ion A wil l be

m i s t a k e n as B and t ha t sampl e s f rom d i s t r i bu t ion B wi l l

be mis t aken as A . The resul ts vary between zero ( th e

tw o d i s t r i bu t ions well separa t ed ) and 0.5 ( t he tw o dis-

t r i bu t ions supe r imp osed) . The c l ass i fi ca t ion ru l e used i sthe best l i n e a r decision r u l e used to c l a s s i f ymu l t ispect ral da ta ( ref . 6-25) .

Based on the resul ts of the pai rwi se ca l cu l a t i on , th e35 signatures w ere aggregated into a s m a l le r n u m b e r ofcomp os i t e s igna tu re s by combin ing g roups o f s igna tu re s

hav ing h igh p rob ab i l i t i e s o f m i sc l ass i fi ca t i on . Classes

de f ined by pho to in t e rp re t a t i on o f h ig h -a l t i tu d e -a i r c r a f tp h o t o g r a p h s and composi te s ignature analyses of S192data can give d i f fe ren t results. Fo r e x a m p l e , for thescene classes ident i f ied on h igh - a l t i t ude -a i r c raf t pho to -

graphs taken in Jun e 1972, there were three nonfores tedwe t l and classes, a f looded forest , brush fields, threetypes of forest crown cover , aspen regenerat ion sites,

and a p i n e p l a n t a t i o n . On the other hand, for the com-posi te s ignature classes of the SI92 da t a ( acqu i red inAugust 1973) of the same scene , there were only tw ononforested wet lan d c lasses and only one general forestclass w i t h th e other c lasses remaining th e same. Timeand seasonal di fferences be tween t he two sets of data

cou l d exp l a in the different groupings. After the catego-ries were selected, th e op t imum spec t ra l bands we rede t e rmined ( t ab l e 6 - I I I ) . Fur the r s tud ie s com par ingL a n d s a t d i s c r i m i n a t i o n w i t h s e l e c te d S 1 9 2 b a n d sshowed th e signif icance of b a n d 11 for i m p r o v i n g p e r-fo rmance as well as the val ue of using more channe l s(i.e., more t han four ) .

Fie ld checks were made to veri fy choices of t r a in ingsets and the i r par t ic ular character . Fin al ly , af ter redef in-in g th e t r a in ing sets on the basis of onsi te inspect ion,

c lassi f icat ion pro bab i l i t ies for each category w ere calcu-lated. The expec t ed c l ass if ica t ion pe r fo rmance for thebest l inear rule c lassi f ie r was calculated.

Figure 6-29 i llust rates the spect ral sep arab i l i ty of the12 classes using the best 2 spect ral ban ds. In th is f igure ,

th e re lat ive locat ion, th e shape , and the orientat ion ofth e d i s t r i bu t ions p rov ide a graphic i l lust rat ion of the i r




TABLE 6-111.—Selection of Optimum Bands for

Composite Signatures From SI 92 Data

Spectral

bond,

u rn

0.41 to 0.46

0.52 to 0.56

0.56 to 0.61

0.62 to 0.67

0.68 to 0.76

0.78 to 0.88

0.98 to 1.08

1.09 to 1.19

1.20 to 1.30

1.55 to 1.75

2.10 to 2.35

10.20 to 12.50

Signal-

to-noise

ranking

( a )

12

1

•

9

•:

-!

10

:

2

, I

Ranking of bands

Seven major

signatures

1

<

1 1

107

1

i

•

:•

:-

Four brush and

tree signatures

•

•

. .

4

-

:7

9

Landsai band

corresponding

to SI 92 band

.

—

•

•

—

-

-

—

-

aTh e highest signal-to-noise ratio is ranked 1.

s ta t is t ica l uniqueness . Th e compute r sepa ra ted theclasses using the six best bands, chose w eighted prob-abilities for the scene (based on co lor- infrared photo-graph ic results) , and determined a threshold value thatcorresponded to the 0.001 level of re jection for sixdegrees of freedom. Pixels having values exceeding th et h r e s h o l d w e r e u n c l a s s i f i e d . T h e a c c u r a c i e s o fclassification range from 72 to 82 percent , depend ing onthe g rouping of the f inal ca tegories and the averaging ofstatistics over 2.6 k m 2. Some l imita tions of accuraciesare expected from th e na ture of the available signal- to-

noise ra tio, the misregistra tion of bands, the geometr icdistor tion, and the scan-l ine-stra ightening procedures.A technique fo r obtaining accurate crop area esti-

mates in agricultura l areas character ized by groundresolution sufficiently large to create a high probabi l i tythat the scanner will integrate a mixture of objects wasdeveloped by N a le pk a et al. (ref. 6-26). Figure 6-30 dis-p lays th e nature of the problem over 2.5 km 2. In this ex-ample , th e n u m b e r of pur e field pixe ls is only 30 per-cent of the tota l pixels that cover the scene. Thus, thei m pa c t of th is technique can be significant, because th emore mixture pixels in a scene, the greater the chancefo r error . Co nvention al c lassif ica tion techniqu es are not

adequate fo r such a case.For this technique, a small num ber of signatures hav-in g suff icient separation are desired not only to avoiddegenerate signatures (one signature equaling a linear

: - • -

*

'

H

I2 0 2 8 3 6 4 4 5 2 6 0 6 8

I n t e g e r c o u n t s , b a n d 1 17 6 8 4

Distribut ion

number

12

34

5

6

Scene class

Deep/shallow marsh

Shrub swamp

Flooded forest

Pine plantation

Dense forest

D istribut ion

number

7

8

9

Scene class

Sparse forest wi th under-

story

Aspen regenera t ion

Ag r i c u l tu r e

10 Brush

without understory 11 Herbaceous

Intermediate to dense 12 Bare soi l

forest with under -

story

FI G UR E 6-29 .—Two -cha n n e l Gaussian representation of the 12

compos i te s ignatures used fo r data c lass if ica t ion . Signatures used

fo r data classification axes represent first tw o o p t imu m wav e len g thbands.

combination of two others) but to keep processing timep r a c t i c a l . P r o c e s s i n g t i m e i s p r o p o r t i o n a l t om(m + l) /2, w here m is the numb er of signatures.

In perfo rmin g classifica tion, signatures based on p ix -els are derived. Fo r best results , center pixels or fieldpixels ar e more desirable fo r avoiding th e ambiguities ofborder points and mixtures . Na lepka et al. (ref. 6-26)identified field pixe ls fo r tra ining purposes by inscrib-ing a sma l l polygon wi th in th e boundar ies of a t rainingfield.

In general , an inset /was defined that is calcula ted by

B + R + L + S pixels (6-4)




w h e r e a indicates the scan direction x or the

a long t ra ck direction y

D a is the size of the resolution cell in the direc-

t ion of a (The S I 9 2 data were oversampled

by 10 percent; therefore, a digital resolution

cell is not equal to a p i x e l . )

Pa is the size of the pixel in the direction of aB is the inset necessary to ensure that th e p i x e l

does not include the boundary between

fields; t yp i c a l l y , B = 0.5p i x e l

Ra is the error due to misregistration effects;

e.g., if one channel is misregistered f rom th e

others b y R pixels, this channel could st i l l b eima g ing across the field boundary when the

o t h e r channels a re imaged entirely w i t h i n

the field. For conic data corrected for

mis reg is t r a t io n , Rx = 0.32 and Ry = 0.

For scan-line-straightened data, Rx =

1 + M sin 9 and Ry= 1 + Mcos 9, wherein

M is the maximum misregistration in con-ical ly scanned data ( found to be 1.13) and 9

is the angle between the line tangent to the

conically scanned data at the point being

considered an d a line in the alongtrack orflight direction. To develop one measure for

the entire scan line, the maximum values of

sin 9 and cos 0, which is 1, are used. Thus,

Rx = 2.13 and Ry = 2.13

L is the error due to field location errors

S is the error due to movement of individual

p ix e l s as a result of the nearest neighbor

scan-line straightening. Therefore, for con-

ical ly scanned data, 5 = 0; for straightened

data, 5 = 0.5 pixel

Thus, the inset to be used for conically scanned data

w o u l d be

Ix = 1 )0.5 + 0.32

= 0.90 + L pixels

/ = ^ 0.5 + 0 + L

= 0.58 + L pixels

(6-5)

The inset to be used for scan-line-straightened data

w o u l d b e

2.13 + L + 0 .5

= 3.21 + L pixels (6-6)

w h e r e / = L = /„.

This technique was ap p l i ed to an urban scene to

determine the amount of vegetative and impervious

ma te r i a l . Such information is usefu l to geographers, ur-ban planners, and urban climatologists. Most pixels

co u ld be mixtures. Five classes of interest were defined:

green vegetation, concrete, other impervious materials

ied center pixels

O H Mixture p i xe ls

Total f ie lds 3 1

Total area 2 4 9 h m2

Total p i xe ls 51 3 (100 percent)

F ie ld center p i xe ls 152 ( 30 percent)

Mixture pixe ls 3 6 1 ( 7 0 percent)

F IGUR E 6-30.—Display of mixture pixels in section 109, Locke

Towns hip , Michigan.




(roofs, asphalt, etc.) , bare soil, an d water . A sta tist ica ltest for a measure of separateness (app roxim ately thedistance, in s tanda rd devia t ions , between th e signaturemean and the hy pe r p l a ne t h r ough the other signaturemeans) showed tha t the f ive classes were degenerate.

Data w ith l imited signal ranges an d less than opt imu mspectra l contrasts are not suitable for mix tur e proc-essors.

Results of this investigation indicate th at , because ofmisregistrat ion in line-straightened data, processingshould be per formed on a conical format. Finer spatia lresolution should be considered for future sensors toreduce th e numb e r of field pixels fo r better training sig-natures. Also, th e design of fu ture sensors should incor -porate a me ans of adjustin g scanner gain and offsetparameters to match the radiance ch aracter istic of in-d iv idua l scenes be t te r so th a t the ava i lab le dyn amicrange is used. Lo ng a tm osph eric p aths add a sizable con-

stant radiance and attenuate th e ref lectance radiance tocause reduced contrast .Signature extension is a process by which the tra in-

ing sta tistics from on e scene may be modif ied and usedto classify features in a second scene that may differ

geographical ly or temporally. Use of this processreduces th e need fo r extensive ground truth and forre t ra in ing s igna tures wi thout incur r ing an intolerableloss in accuracy. Nalep ka tested several signature-exten-sion algorithms on the S192 data (ref. 6-26). The datawere grouped into 10 clusters that w ere identif ied fromt raining statistics. One of the first methods a t temptedinvo lved dark-object signature correction. The tech-nique assumes , band by band, tha t th e signal levelsgenerated by dark objects represent mostly path ra-diance and can be used to generate a correctionalgorithm. Because of the haze, th e correction factort ends to be greater as the wave length becomes shorter .Significant im pr ove m e n t in classif ica tion accuracy oc-curred; in pa r t icu la r , th e recognition w as unexpectedlyaccurate where the haze was densest (i.e., the dark levelcor rec t ion w a s gr e a t e s t ) . H ow e ve r , th e a l g o r i t h mshowed some tendency to misclassify br ight features asdarker features. The need for a mul t ip l i ca t ive signaturecorrection in conjunction with an additive correctionfeature w as made evident.

A second method, involving an adjus tment for themean level of the signal over an extended scene, wast r ied and produced slightly less successful results. In thet echn ique , the co rrela tion between averages over por-t ions of the tra in ing scene and of the signature-exten-

sion scene is used to estimate a correction for the meanlevels of each t r a in ing s igna ture in each band. Themethod required similar percentages of ground cover .The results showed nearly th e same correction factorfo r th e shorter w aveleng th bands, a l though differenceswere noted a t the longer wavelength bands. This resultsuggests a bias in favor of darker mater ia ls , which ab-sorb shorter wavelengths; at longer wavelengths, th escene has more contrast and vegetation is more reflec-tive.

A t h i rd method incorpora ted both a m ul t ip l i c a t iveand additive signature correction (MASC) factor byus ing a least squares regression to match t r a in ing c lus te r

mean signal levels with local cluster mean levels basedon the ordering and spacing of those signature meanswi t h i n a chosen data band. Because mathematicalmodeling of the i l lum ina t ion va ria t ions indica ted tha tthe va r ia tions should be both mu l t ip l ica t ive and addi -tive, use of MASC was expected to produce a realisticsignature correction factor . A test pe rformed using onlyth e 1.55- to 1.75-/im band fo r classifying a Michiganagricul tural test si te showed that more than one bandshould be used to help match the clusters from differingportions of an extended scene. W hen there are var ia-t ions a longtrack, c luster ing a lgorithms cannot be ex-pected to produce sets of signatures from two differentscenes tha t are in close correspondence; some m e thodis needed to identify and omit noncorrela ting clustersdur ing the cluster- matc hing procedu re that leads tocalculat ions of signature correction factors.

Simonett (ref. 6-27) used the S192 data to extractland use inform ation . Con trast-enhanced, geom etr ica llyrectified gray-level maps for the test areas were printedfo r the spectra l bands (4 and 8 ) prov idin g the greatestvisual discrimination of land use (cover) categories.Noise-reduced, line-straightened data were used an dreformatted for fur ther analysis. Con trast enhanc ementwas accomplished by a technique called histogramequal izat ion (ref. 6-28), in w h i c h a nonlinear (several to




one ) ma pp ing o f i npu t g ray leve ls t o ou tpu t g ray l evel sis def ined and the input data are effect ive ly spreadacross th e en t i r e usab l e dynamic r ange of the o u t p u td isp lay . Because only land use was of interest , only therange per t inent to land features in a given spect ral band

w a s t r a n s f o r m e d . Th e o u t p u t p r i n t m a t c h e d th e scale of

U.S. Geological Survey (USGS) 7.5 ' quadrangle mapsfo r ease i n com par ing re su l ts w i t h ground t ru th and inse l ec t ing compute r t r a in ing sites.

Fin a l ly , ground- t ru th and scanne r d ig i t a l da t a we remerged by generat ing a data f i le consist ing of map in-

fo rmat ion on fie ld bounda r i e s , land use boundar i e s , and13 spec tra l da t a va l ues. Thus , w i th in each ind iv idua lrecord of the data file, the ana l ys t h ad access to the gray

l evels from al l S192 band s, the p ixe ls tha t were assignedto k n o w n f ie lds , and the l and use represented by thep ixe l s . The 22 SDO's were reduced to the best 13spect ral bands based on a selection process.

Field signatures were computed to give th e m e a n s

and the covar i ance mat r i x , a nd a signature f i le wasgenerated. By means of a s tepwise d iscr im inan t analysistechnique ( refs . 6-29 and 6-30), th e best set of spectralbands fo r d i sc r imina t ing var ious l and use categories w asfound. Composi te group signatures (a funct ion of how a

given scene is to be d iv ided) we re used to calculate a setof cross-product terms t o fo rm a m at r i x fo r bo th w i t h i n -

group cross produc t s and to tal cross products . Th e totalcross-product matr ix w as d i rec t l y p ropor t iona l to thevariance-covariance matr ix for al l the data treated as asingle data set . Th e wi th in - g roup c ross -p roduc t ma t r i xw as d i rec t l y p ropor t iona l to a weighted sum of thevariance-co variance m atr ix for each group. A given

spec t ra l band p rov ides a good d i sc r iminan t be tweengroups if the to tal var iance for all the data (diagona l e le -m e n t of the t o ta l c ross -p roduc t ma t r i x ) is much greater

t h a n th e variance obtained b y t reat ing th e data ingroups (d i agonal e l ement of the wi th in -g roup c ross -p roduc t ma t r i x ) . Spec tra l va l ues are assumed to h a v e am u l t i v a r i a t e Gauss ian d i s t r i bu t ion th roughou t . Th e bestspec tra l band fo r d i sc r im ina t ing among a l l g roups wasselected b y calculat ing th e l ike l ihood rat io to test th eequal i ty over all groups fo r each spect ral band. Theprocess is repeated to find successive combinat ions ofbands t ha t d i sc r imina t e best among groups, given that

specific bands have a l rea dy been selected. In a p p l y i n g

th e s t epwise d i sc r iminan t ana l ys i s , on l y th e best f ie ldsignature represent ing the group se lected for analysis

w as used. In a d d i t i o n , an est imate of the spectral sepa-rabi l i ty of the input data c lasses at each step w as madeusing the t ransformed divergence measure ( ref . 6-31) .

The t e c h n i q u e w as used to e x a m i n e 87 test si tes withsignatures calculated for 609 fields and to separate themin to r e l a t i ve l y b road l and use classes ( L e v e l I ) — u r b a n ,agr icu l tural , forest , water , and wet l ands—and morespecif ic l and uses (Level I I ) .

For the broad c lassi f icat ion, f ive bands we re found tobe impor t an t . These bands we re 11, 9, 13, 5, and 6, inorde r of decreasing value . Again, spect ral coverage inth e near infrared, together w i th t he red and t h e r m a l - i n -frared bands, proved to be crucial .

Fur the r examinat ion to de t e rmine separab i l i t y w i t h -

in each broad class w as unde r t aken . Howeve r , th es imi la r i ty of the spect ral s ignatures fo r Level I classes,

th e compl exi ty of the spat ial dist r ibut ion, th e l ack ofmul t i da t e coverage, th e presence of noise, misregist ra-tion, and d i f fe ren t samp l ing ra t e s be tween channe l s in -

fluenced th e final outcome. The best results were ob-

tained fo r large fields, in w h i c h some of the effects werenot as i m p o r t a n t . In general , th e best five b a n d s fo r dis-

c r imina t ing th e general classes were not the same bandsfo r d i sc r imina t ing e l ement s wi th in a class; therefore, atwo-stage processing technique w as i m p l e m e n t e d .

In the first stage, an u n k n o w n p i x e l s ig n a t u re w asassigned to one of f ive general levels and t ha t i n fo rma-

tion was stored. In the second stage, the best five

spect ral bands fo r d i sc r imina t ing wi th in one of the f ive

general levels were selected. A maximum-l ike l i hoodclassification algorithm w as used during each of the twostages wi th equa l a p r io r i probab i l i ties assumed fo r each

class.

Natura l g roup ing of signal levels, or cluster ing, w asalso tested. Th e distance measure used in the cluster ingis th e reduct ion of the divergence measure for anassumed d iagonal covar i ance mat r i x . Use of th is pro-cedure reduced computer-processing t ime bu t resultedin some loss of d i sc r imina t ion . The invest igat ion

revealed th e val ue of mul t i da t e image ry because of thecharacter of ou t l y ing e lements wi th in ce r ta in g roups .






S c a l e , k m

K e yW h i te - s n o wLight b l u e - D o u g l a s firD a r k b l u e - w a t e rM e d i u m g r e e n - p o n d e r o s a p i n eD a r k g r e e n - spruce-fir

D a r k b r o w n - soil a n d e x p o s e dr o c k o u t c r o p

O r a n g e - b r o w n - a s p e nY e l l o w - g a m b e l o a kR e d - hay and pasture

B l a c k ( u p p e r r ight c o r n e r ) - null d a t a

F I G U R E 6-32.—Comparison of "per point" an d ECHO classif ica tion results fo r forest cover types, (a ) Per-point classification, (b ) E C H O

classification.

and then classifies th e area wi th in th e b o u n d a r y as asingle spectral c lass. The c lassifier specif ies the bou nd-

aries as p a r t of the procedure and is not d ep en d en t onth e ana lys t fo r spec i fy ing boundar ies. Th e outpu t fo r -mat proved acceptable to those agency personnel in-terested in a general ized co ver - type ma p. The c lassifica-t ion resul ts of the two approaches are shown in f igure6-32. Th e per -point c lassif ier resul ts do no t h a v e th esmooth ing effect s h o w n by the EC HO classif ier resul ts .

Overa l l evaluation of computer processing revealedthat four -band c lassif icat ion w as opt imal f rom th es t a ndpo i n t o f best accuracy an d least expense; a signifi-

cant increase in classif icat ion costs resul ted f rom an in-

crease in the n u m b e r of bands beyond four . However ,for different classes of objects , var ious combinations of

four waveleng th bands were needed fo r accurate dis-cr imina t ion . Thus , fu tu re satel l i te sensors should oper -a te with more than four bands b u t need to ana lyze wi thonly a subset of four bands, depending on the scene

com posit ion. For exam ple, in analyz ing a land use(forest cover) scene, 85 percent overal l c lassif icat ion ac-curacy was achieved using the four bands located at 0.46to 0.51, 0.78 to 0.88, 1.09 to 1.19, an d 1.55 to 1.75 fim.

Acreage est imates of forest cover types w ere high lycor re la ted wi th measurements f rom s tandard pho to in -terpretat ion techniques. Th e va lue of the techn ique in




which s lope and aspect were monitored together withth e s p ec t r a l s i g n a t u r e w a s p r o v ed w h en s p ec t r a ldif ferences between forest cover types were found to beinf luenced signif icantly by topograph ic r e la t ionsh ips ,whereas spectral var iat ions within individual foresttypes were related to dif ferences in s tandard density .Th e cons idera t ion of these factors resulted in a substan-tial imp rovem ent (10 percentage po ints) in c lassifica-t ion performance.

A n evaluation of the pr io r i ty for the var ious bandssuppor ted the use of six bands (spaced two in the visi-ble, two in the near infrared, one in the middle in f ra red ,and one in the thermal in f r a red) for the app l ica t ion a readefined as land use and forest cover . W hen th e tech-niques were appl ied to the m a p p i n g of hydro log ica lfeatures, th e d i f f eren t classes of snow were tabulated asa func tion of elevation and spectral s ignature. This c lassdif ference arose f rom var ious mixtures of snow an dforest cover w ith in each scanner resolution elemen t andpossibly f rom snow-melt ing condit ions.

The "layered classifier" approach w as used and pro-vided better dif ferentiat ion between snow an d cloudsand better snow-cover class tabulation by comparisonto c o n v e n t i o n a l m a x i m u m - l i k e l i h o o d c l a s s i fi c a t i o ntechniques. The thermal - in f r a red band p roved va luab lein measur ing reservoir tem peratures accurately af ter atwo-point nonlinear cal ibrat ion technique w as used toprocess th e SI92 data. The high elevation of the reser-voir and the t ransmission character is t ics of the 10.2- to12.5-//.m band led to close agreement between satel l i temeasurements and reference measurements for thesame por t ion of the reservoir.

A tabulat ion of the watershed area extent of eachspectral class of snow indicates that remote-sensingdata can be effectively used to predic t water runofffrom mountain snowpack areas. O n a regional basis,this information would aid reservoir and watershedmanagement planners .

T homson (ref. 6-33) inv estigated th e effects of var ia-tion in the atmospher ic state on pattern recognition per-formance. The question of wh ethe r preprocessing m ustbe altered along a flight track is crucial to the success ofsignature extension. Based on a comparison of resul ts

obtained using a combination of four -band optimumsets, a Landsat analog, an d opt imum seven-band setsfrom th e SI92 sensor, th e fol lowing conc lus ions ar enoted.

A t a tmospher ic cond i t ions equ iva len t to hor izon ta lvisibilities of a p p r o x i m a t e l y 10 km, adequate per fo rm-ance (greater than 65 percent correc t c lassif icat ion ) canb e achieved with in vis ibi l i ty var ia t ions of ±3 to ±4km. I f greater var iat ions are found, data-preprocessingcorrect ions must be made to main ta in adequate per -formance. A s better sensors ar e constructed, more caremust be taken in selecting a set of bands and in deter-min ing the i r number and location. Fo r example ,al though seven optim um band s gave better perfo rm-ance under noise-free conditions for a given set of en-v i ronmenta l fac tors than did four opt imum bands , theseven-band resul ts were m ore sensitive to changes in at-mospher ic vis ibi l i ty .

In a nalys is of S192 data, W iegand et al. (ref. 6-34)used the 0.78- to 0.88-ju.m band to visual ly d i f f eren t ia tewa ter , vegetat ion, and bare soil on a cathode-ray tub e ina s tudy of eight saline areas in southern Texas. Simplelinear correlation analyses were used to relate fieldelec tr ical conductivi ty EC e measurements to the meanmultispectral scanner digital values for both bare soilsan d vegetation test areas. In one test area, bands 6 to 11of th e multispectral scanner correlated well , but thedifference between the signal from bare soil and vegeta-tion in the 1.2- to 1 . 3 - / L i m band (in Landsat , 0.8 to 1.1/im) correlated best with th e a m o u n t of electrical con-duct ivi ty or sa l in i ty .

Hannah et al. (ref. 6-35) used SI92 CCT's to obtain

land use information for Or lando and Lakeland,Flor ida. Band 13 imagery indicated that commercial - in-dustrial regions, newly formed residential areas, an dwooded residential areas could be separated on the basisof temperature. The land use maps p repared fo r theseurban areas we re der ived f rom analysis of bands 4,6,11

or 12, and 13 . The m axim um -likel iho od proced ure wasused principal ly, al though less accurate schemes fo rclassification were applied. These schemes were basedon measurements of least distances from th e p o i n tbeing classified and on determination of the three




Spectra l band Xj -

F I G U R E 6-33.—Geometr ic interpretat ion of m e a n s of s ignaturem i x t u r e s . In the case i l l us t r a t ed , th e u n k n o w n A' is a m i x t u r e oft h r ee pure mater i a l s . A, B, and C, w h i c h form th e ver t ices of the sig-n a t u r e s implex .

nearest classes by least dis tance and use of m ax im uml ike l ihood to choose a m ong them.

In a d i f fe ren t a p p r o a c h , M c M u r t r y a nd Petersen (ref .6-36) used wa ve- num ber analy s is . Each ban d inspectedin t he Four ie r t rans form dom ain was foun d to prov ideu n i q u e w a v e - n u m b e r in f o r m a t i o n a b o u t p a r t i c u l a r

scenes . This method is suggested fo r s t udy i ng l ine a -ments and geologic s t ructures such as folds and fracturetraces.

If th e l ineaments are rela ted to fractu re t races and ap-

pea r as a l ine of di scont inuous sp ikes in intens i ty rela-t ive to the sur rou ndin g in tens i ty , t hey will have the dis -t i nc t ive wa ve num b e r k (k = 1 / X , whe r e \ is spat ia lwave l eng th ) response for a l ineament f rom k = 0 tot he N yqu is t wave nu mb er . Severa l f i lt e r func t ion s canalso be used w ith this metho d. For geology, a f i lter func-

t ion called th e s tr ike-select ive filter can b e used to checkfo r l ineaments first observed by photoin te rpre ta t ion . Ifth e l ineaments exis t , th e digi ta l format can be enhancedas shown in reference 6-36. Other features can a lso beenhanced by us ing this method (ref . 6-37) .

Func t ions tha t take the de riva t ive of the s ignal suchas h igh- and low-pass f req uency fil ters can also be ap-pl ied. Fil ter analys is can a id in de c i d ing wh i c h b a nds touse for the ana lys is of a pa rt icu lar para me ter and canaid in select ing a subset of b a nds fo r color d i sp l ays .

In a t e c hn i q ue first out l ined by H or wi t z et al . ( re f .

6-38), a p r opo r t i on e st i m a t ion a l go r i t hm is used to esti-m a t e th e percentage of area occupied by d i f fe ren t ob -jects w i t h i n t he f i e ld of v iew (FOV) . Geomet r i ca l ly ,three objects as seen in two spectra l bands can bedepicted (f ig. 6-33). Points A, B, and C represent thepure spectra of each object . If an ins tantaneous FOV

c on t a i n s a m i x t u r e of al l three materia ls , then th e sig-na t u r e X m u s t li e w i t h i n th e t r iangle formed by con-nect ing the vert ices at A, B, and C. By ex tending a l inef rom one ver tex through th e u n k n o w n p o in t w i t h i n th et r iangle and intersect ing the opposi te s ide, an es t imateof t he pa i rwise propor t ion of the pure ma te r i a l s con-s t i tu t ing the unknown e l ement can be made by t ak ing

the inverse ra t io of the lengths into w hic h the leg isd iv ided .

Th e c onc e p t can be ex tended in to /V-dimens iona lspace so t ha t a t least N -1 spectral bands of i n f o r m a t i onar e requi red to es t ima te mix tures of T V objects satisfac-to r i ly . Some degrada t ion in es t imates is expected if onemateria l is very s imilar to the weighted average of theothers .

The va lue of the S192 spectra l resolut ion w as de m on-s tra ted by Poul ton a nd W elch (ref . 6-39) , in the s tu dy ofr ice -yie ld predict ion. The crop calendar for r ice beginswi th a ba re unf looded s tage , progresses to a ful ly greenvegetat ive s ta te , and e ve n t ua l l y becomes a c ha ng i ng

yel low dur in g r ipening . Thus , spec t ral d i s c r imin a t ion a tt he proper season was found to be a dominant fac tor .For a test area in Louis iana , in te rpre ta t ion of an S192color composi te yielded a higher accuracy than didana l ys i s of the SI 90A and S190B photograph s t aken atth e same time. Figure 6-34 is a compar i son of the threeimages . The Sk ylab S192 color composi te us ing bands 1,7 , and 9 had bet ter contras t and thus a ided in thedif ferentia t ion of rice in var ious stages of matur i ty f romother c rops when the field size w as greater than 6 to 8h m 2 .




0 5

S c a l e , k m

F I G U R E 6-34.—Data taken in A u g u s t 1973 of the Louis iana coas tal plain r ice region. Note th e i m p r o v e m e n t n field contrasts in the S192 colo rc ompos it e c om pared to the c o nven t iona l pho tograph ic p roduc t s. ( Or ig ina l scale, 1:327 000.) (a) S190A colo r (SL3-22-120). (b) S190B color(SL3-83-OS6). (c) S192 color composite.

In geology, Goetz et a l . ( ref . 6-24) separated differ ent

l i thologic uni t s mos t effectively by us ing bands ou t s idethe range ava i l ab le in the c ur ren t Landsa t reg ions . Theyfound that bands 0.46 to 0.51, 0.98 to 1.08, and 1.20 to

1.30 fj.m f rom both field spec t ra l ana lys i s and enhancedcolor comp osi tes gav e the bes t separat ion (f ig. 6-35) .For th i s pa r t i cu la r s i t e , t hemat i c maps produced bythree class if icat ion a lgori thms were not as accurate asresul t s ob ta ined by photo in te rpre ta t ion of compute r -enhanced i m a ge r y . A m ong th e three a lgor i thms t r i ed ,th e l inea r -d i s c r iminant a lgor i thm seemed to be themost ef f i c i ent . The need for operat ion al sa tel l ites capa-b le of imaging in the far - ref lect ive- inf rared region wasexpres sed .

Hous ton et al . (ref. 6-40) investigated th e po t e n t i a l ofS192 data by us ing both v i sua l qua l i t a t ive exam ina t ionand dens i tomet r i c quant i t a t ive measurements . Ex cep tfo r th e detect ion of red beds in band 2 (0.46 to 0 .51 /^m )and b et ter contras t o f sm al l , c losed a nt icl ines in ban d 4

(0.56 to 0 .6 1 M m ) , th e nea r - inf ra red bands provid ed th e

best contras t fo r dif ferent rock uni t s (band 8 , 0.98 to1.08 / i tn; and ban d 9,1.09 to 1.19 urn) . Rel at ive densi tyvalues for 15 l i thologic uni ts on each S192 band weremeasured by a video densi tometer , and resul ts showedtha t bands 7, 8 , and 12 yie lded th e highest tota l contras tva lues . Co mp ute r ana lys i s of the SI92 data fo r geologicappl icat ions c onf i r m e d th e va lue of the nea r inf ra red inenhanc ing cont ra s t be tween l i tho logic units . The d igi ta l

F I G U R E 6 -35 .—Enhanc ement s of geologic uni ts by S192 compositecompared to S190 photographs , (a ) Simpli f ied geologic map of theCoconino Pla teau s howing d i s t r ibu t ion of geologic un i ts , (b ) S190A

fa lse-color- infrared compo si te pho tograp h. The green band is dis-played as blue, the red band as green, and the inf rared band as red.The s tream in the upper por t ion of the f rame is Catarac t Creek.(c ) S192 false-color com posi te ma de from bands 2 , 8, and 10. Areaincluded is s l ight ly less than that shown in figure 6-35(b). —»-




c°If l f « ( J f l

15

Scale, km

DAl luvium, reworked Tertiary gravels,

an d Ter t iary grave ls

Basalt flows, landslides, an d

basalt talus

Unconformity

D

M oenkopi F ormation

la) « 5

Unconformity

D olomite: unit 6

Sandstones and shales ( local ly g ypsi ferous)

with underlying dolomite: units 4 & 5

DSiltstones an d shales ( local ly gyp si ferous)

with underlying dolomite: units p, 1, 2, & 3

Older Paleozoics

- Contact, dashed where approx-

imate

-?-. . . Fault , dashed where approx imate,

dotted where concealed, queried

where uncertain; bar and dot

on downthrown side

-?-- M onocline, dashed where approx-

- imate, queried where uncertain;arrow indicates direction of in-

clinat ion

-|—- Ant ic l ine , showing plunge ofax ia l trace

-)—- Syncline, showing plunge

of axial trace




Sca le , km

FIGURE 6-35.—Continued. \




Scale , km

FIG U RE 6 -3 5 .—Co n c l u ded .

\




tapes for the 13 S192 bands were analyze d by co nst ruct -i n g a l p h a n u m e r i c m a p s a n d c o m p u t i n g p a i r w i s e

c l us t e r s f rom two-d imens iona l f r equency h i s tograms of

test sites. His tograms fo r each of 78 possib le pai rs f rom

13 bands we re ana l yzed , and maps were made of thebest contrast pai rs . A fur ther analysis of ref lec tance

vectors for the test region resulted in a decision to useweigh t ing factors . O ne p a r t i c u l a r method, designated Q -mode fac to r ana l ys i s , w a s conduc ted w i th more t han100 000 po in t s , and re su l t s i nd i ca t e t ha t t h i s me tho d i susefu l . I f ma t r i x D i s an m by m (m = r i ) da t a ma t r i x o f

ref lec tance values in the / - t h channe l fo r t h e y - t h p i x e l ,th e c o l u m n s of m a t r i x D wil l b e normal i zed to u n i t

l eng th L by t he fo rmul a

(6-7)

repre sen t ing th e square root of the sums of e a c h m a t r i xe l ement squared , and by the new mat r ix

D

' (6-8)

Each co l umn of ZQ represents th e reflectance at a given

locat ion af ter it s brightness has been adjusted to thesame gene ra l i n t ens i t y .By t a k i n g th e cosine of the angle be tween tw o nor-

mal ized ref lec tance vectors, a test of s i m i l a r i t y is easilymade. The cosine wil l have a v a l u e of 1 if the vectors areident ical and wil l have a val ue of 0 if the vectors a red i f f e r en t ( p e r p e n d i c u l a r l y ). A c o m p u t e r a l g o r i t h m w a sdeveloped that fac i l i tated factor comparison ( ref . 6-40)

of l arge numbers of p ixe l s b y Q-mode analysis . Table6-IV is an e x a m p l e of the f ac to r s computed by the Q-mode method fo r v a r y i n g w a v e l e n g th A. The use of thefac to r s i n mak ing a new a l phanumer i c map shows th em a n n e r in w h i c h o u t c ro p s of enr i ched rocks cou l d b eenhanced or the densest vegetated areas could bedel ineated.

Haefner ( ref . 6-41) found that , fo r ope ra t iona l map-p i n g of dynamic f ea tu re s such as snow, p re fe rencesh o u ld be given to digi ta l data to t ake advan tage of near -real - t ime c lassi f icat ion. B y c o m b i n i n g i n f o r m a t i o n from

b a n d 11 (1.55 to 1.75 / im) , band 7 (0.78 to 0.88 / u rn ) ,

and band 2 (0.46 to 0.51 /u.m), snow could be separated

f rom clouds. The test area wa s f i rst c lassi f ied int o 29d i f fe ren t categories but later reduced to 5 m ain classes:s n o w in Sun, snow in shadow , c l ouds , snow-f ree a rea inSun , and snow-f ree area i n shadow. D ata w e re p reparedf rom digi ta l tapes fo l low ing th e s t andard p rocedure s of(1 ) da t a r e fo rmat t i ng to match a va i l ab l e com pute rsystems, (2) de l ineat ion, (3) s tat i s t ical evaluat ion of

sampl ing areas, (4 ) classi f icat ion of classes based oneuc l idean d i s t ance , and (5) da t a d i sp l ay w i t h geometr ic

correct ions fo r m a p l i k e o u t p u t .Goldm an an d Hor va th ( ref . 6-42) researched the

detect ion of o i l spi l l s on the ocean w i t h S192 data, whic h

were expected to be useful for this app l icat ion because

of the spect ral resolut ion choices and the wide area ofeffective coverage (68.5 k m ). Diff icul t ies were expectedbecause of the u nc er ta inty in the na ture of oi l - to-back-ground contrast . Sl icks that have a center thick enoughto inh ib i t th e d i f fus e upw e l l ing r ad i a t i on f rom th e wate rwoul d appear darke r t han th e su r round ing wate r .

Because oi l has a higher specular ref lec tance than thato f wate r , th e wate r m a y b e dark and t he spec ular ref lec-tance of the oi l may dominate ; in such cases, the oi lwould appear br ight in contrast against the background.C h l o r o p h y l l and suspended par t i c l e s compl i ca t e t hespect ral contrast fur ther . In almost al l cases, h o w e v e r ,fo r moderate - thickness f i lms, the ref lect ivi ty of at least

th e t h in por t ions o f o i l on wate r shou l d be un i fo rm l yhigher than tha t of water alone . Techniques for rat ioingtotal radiance values f rom one band to another can he lp

separate these effects and p e r h a p s be used to c o n f i r mthe location of an oilspi l l .

Statistical analysis of the noise in the SI92 data waspe r fo rmed be fore th e detect ion method w as a t t e m p t e d .

Mean values and s t andard dev ia t ions we re computedfo r a test area. Th e resul ts showed that a smal l ref lec t ive

a n o m a l y c o u l d n o t b e detected w i t h s i n g l e - b a n danal ys is on l y .

Spat ia l ly coheren t weigh ted sums we re generated toreduce noise effects using four channels (SDO's 3, 7, 9,and 15). W e igh ted sum ma t ions , i nco rpora t ing r a t ios o fthe s t and ard dev ia t ion , equa l i zed t he no i se con t r ibu t ion




TABLE 6-IV.—Summaryof Eigenvalues an d Factors Computed by Q-Mode

Analysis of Hyattville, Wyoming, Area SI92 Data

/

12

345

67

89

10

11

12

ij

b'

<y

Factors

1st' 2db

0.10240 0.18692

.14507 .28924

.12920 .28356

.13420 .35157

.12151 .28651

.51754 -.23440

.16102 .40116

.15241 .31609

.62774 -.37827

.32864 .06362

.16681 .35972

.26852 -.05455

- 1; X. - 0.98844 urn.

- 2; \j- 0.00517Mm.

- 3;X . - 0.00203Mm.

3d'

-0.23624

-.45414

.23215

-.22595

-.34220

-.19352

.32231

.36925

.27163

-.25477

.31071

-.05456

4th*

-0.09554

-.19125

-.01564

. 11777

.11615

.73040

.11809

.00438

-.26939

-.36177

.06647

-.41396

Band

G r e e n yel low (0.56 to 0.61 tu rn)

Or an g e r ed (0.62 to 0.67 /im)

N e a r i n f r a r e d (0.78 to 0.88 jtm )

M i d d l e i n f r a r e d (1.55 to 1.75 fim )

M i dd l e i n f r a r ed (2.10 to 2.35 /urn)

T h e r m a l i n f r a r ed (10.20 to 12.50 /*m)

N e a r i n f r a r ed (1.20 to 1.30 ^m)

N e a r i n f r a r e d (0.98 to 1.08 /xm)

Thermal infrared (10.20 to 12.50 /im)

Viole t blue (0.46 to 0.51 urn)

N e a r i n f r a r ed (1.09 to 1 . 1 9 M m )

Violet (0.41 to 0.46 /j.m)

dj' - 4; X - 0.00148/i

of a ll channels used in the summation. Values of the

sums fal l ing within th e highest and lowest 1 0 percent of

th e range were isolated an d designated special points. If

an oilspill were present in the scene analyzed, it would,

w i t h high probability, have special points adjacent to

each other.

Because th e results over a 600-pixel area gave only arandom distribution, no oi l sp i l l could be confirmed.

H o w e v e r , the technique proved valuable becausecon-

firmation of an oilspi l l with Landsat bands 4 an d 6 was

successfu l when ratios of radiance were taken after

su b t r ac t in g th e background radiance from a l l values in

the scene.

Pi r i e an d Steller (ref. 6-2) studied coastal circulation

and sediment loading using S192color composites of

images specially prepared b y a linear expansion of theimag e density range so that contrast was enhanced for

s m a l l density changes. Bands 4, 6, and 7 were used to

enhance interpretation in analysis of coastal processes

(fig. 6-36). Th e detail seen in the enhancement is con-

sidered unique. Variations in suspended-sediment load

are easily seen, and comparisons to known sediment-

distribution maps show close correlation. Areas on the

enhancement that appear to be receiving the greatest

amounts o f surface sediment closely correspond to the

areas of maximum deposit as seen from ground-

sampled surveys.

Water-depth relations were established from analysis

of SI92 visible band ima ge ry b y Trumbull (ref. 6-43)

and by Polcyn and Lyzenga (ref.6-44). Band 3 (0.52 to

0.56 / A O I ) w as most useful fo r water penetration; colorcoding b y Polcyn improved contrast which aided in

rela t ing data values and water depth. Further discus-

sions are presented in section 5.

Imagery Use in Earth Resource Models

The 13 SI 92 bands have provided investigators a

wide range of spectral data for study of Earth resources

w i th predictive models. T h e examples discussed in this

section illustrate the use of S192 imagery in models that

a re used to predict climate changes, wind fields, a t-

mospheric effects, and soil moisture.

DATA ANALYSIS TECHNIQUES 307



/

S c a l e , km /

F I G U R E 6-36.—Color composites made from S192 computer tape data of northern Cal i fornia . These enhancemen ts were made by merging andcolor-f i ltering l inearly st re tched Skylab comp uterized images of three scanner b a n ds . Ea ch b a n d wa s i n d iv idu a l l y f i l tered to maximize sedi-

m e n t t ransport an d su r fa ce - cu r ren t characteristics, (a) San Pablo Bay . (b) The Russian River-Bodega B ay area.

A l e x a nde r et al.2

used th e t he rma l band of the S192to cons t ruc t obse rved- tempera ture maps fo r com-par i son wi th predic ted- t empera ture maps produced byuse of a surface-cl imate s imulat ion model . By consider-in g the effect of land-use-rela ted components of urbancl imates (such as the heat-is land effect) , bet ter informa-

t ion on c l ima to logica l consequences of land use changescan be derived from th e model and future urban des igncan be m a de m or e effect ive. T his model enables ex-t rapo lat ion of remote-sensing resul ts a t a given t ime toother t imes of the day or yea r whi l e a l lowing fo rchanges in the input pa ramete rs . Da ta ob ta ined by animaging radiomete r enab le cons t ruc t ion of a ma t r ix ofspat ia l averages over a l l types of urban surfaces that isfa r super ior to point -sampl ing tables . Earl ier researchh ad demons t ra ted th e va l ue of t ime-sequent i a l remote lysensed data . The s imula t ion mode l is based on the

Robert H. Ale xan de r, John E. Lew is, J r . , e t a l . , "App l ica t ions ofSk y lab Data to Land U se and Cl imatologica l Analysis ," unpu bl ishedFinal Repo r t , N A SA -U SG S A g reem en t T-5290-B , 1976 .

famil ia r energy conservat ion equat ion rela t ing

R + S + H + L = 0 (6-9)

where net radia t ion R, soi l heat flux S, sensible heatflux H, and la tent heat f lux L are expressed in terms ofmeteorological -geographical parameters and surfacetempera ture . A t e m pe r a t u re e q u i l i b r i um m ode l is usedto search for the specif ic surface temperature that bal -ances the equat ion. Profi les of soi l temperature as afunction of depth a re upda ted after each i tera t ion. TheSkylab E R E P e x p e r im e n t led to i m pr ove m e n t s in a sec-ond vers ion of the model that incorporated es t imates ofgeographical terra in parameters in the form of (1) wet-ness fract ion ( i rr igated lawn cover and t ree cover) , (2)s i lhouet te ra t io ( the ra t io of the vert ica l s i lhouet te areain a t rac t to the hor izon ta l a rea of tha t t rac t ) , and (3) ob-se rva t ion heigh t (mean vert ic a l heigh t tha t obstructsa irf low and also increases the area of absorbed radia-t ion) . These factors were even more valuable becauset hey cou ld be deduced from rem otely sensed imagery .




From space, t he t emp era tures def ined for a p ixe l canbe ambiguous when several objects are in the sameresolu t ion e l ement . To c a l ib ra te the s canner , a m ethodis used to a c c o u n t for the a t m os phe r i c pa t h in f lu en ce onsur face - t empera tu re es t imates . A gr a y -wi ndow m ode l(ref. 6-45) w as used in the f o r m

(6-10)

whe r e R z is the radian ce in w at ts per cent imeter squaredmicrom ete r s t e radian rece ived by the spaceborne s can-ner, R0 is the surface radiance, E is the emissivity of the

a i r p a t h , an d [E b b (T)} i s the e q u i va l e n t b l a c k -b ody ra -

diance of the a i r pa t h at mean tempera ture T.

Both a tmospher i c pa th convec t ions and two- ta rge tt empera ture -ca l ib ra t ion procedures were used to f inal ly

re late scanner digi ta l values to t rue surface tem-

pera tures . T h e resul ts were encouraging. How ever,when the mode l predic t ion and S I92 t empera ture mapswere compared , the mode l produced va lues lower thanthose observed. Fur the r re f inements of the mode l andbet ter class if icat ion of land cover are recommended.T h e u s e o f c o m p u t e r - d e r i v e d c l a s s i f i c a t i o n f r o mmul t i spec t r a l scanner data w as considered a promis inga l t e rna t ive .

Villev iei l le and W eiller's (ref. 6-46) use of models

concerned the evaluat ion of vert ica l wind profi les . Theconvect ive cel l in the a tmosphere can be considered as t a ti ona r y phe nom e non t ha t is spa t i a l ly repe t i tive w i tha n in te r ior s inusoida l v e r t i ca l win d va r i a t ion a long th e

ver t ical ax i s and two perpendicula r hor i zonta l axes.One exam ple of a wind f ie ld W wou ld be

W = W m cos ( l x ) cos (m ) sin (nj (6-11)

fr ic t ion forces were considered, and wi nd p r o f i le s at thein te r io r of the convec t ive l ayer were ob ta ined for agiven cha rac te r i s t i c d imens ion . Th e m e t hod w a s a p -plied us ing S190B da ta ob ta ined over Bord eaux , F rance ,to de te rmine spac ings L K a nd L y Values o f otherp a r a m e t e r s needed w ere ob ta ined f rom radiosond e

measuremen ts . F igure 6-37 shows a c om pa r i s on of thepredic ted prof i l e and t he actua l prof i l e as measured byrad iosonde .

The c e ll t y pe de te r m i ned t he m i n i m um i n te r va lenergy di s s ipa t ion . T h e resu l t s war rant fu r the r c om -parisons . If successful , inters t reet spacing and s treetd i rec t ions de r ived f rom sa te l l i te measurements couldbe coupled with mean thermal gradients derived fromsurface t empera tures suppl i ed by a very high resolut ionr a d i om e t e r o r other future sa tel l i te sys tems to m a k efeasible the operat ional use of the model .

Aldrich e t al . (ref. 6-47) used an a ircraf t to obta insatel l i te-matched fores t terra in-reflectance measure-

ments so that correct ions for a tmospheric effects couldbe made . The a ircraf t pla t form a f forded more ve r -sa t i l i ty t han would a t owe r -m oun te d i n s t rum e n t , wh i c hcan only m easure s ignatures over an area equiva lent to afe w pixe l s of sa te ll i te da ta . W i th m ul t ida te coverage , th epossibil i ty of measur ing t ime changes in vegetat ivespectra l s ignatures was feas ible . Also, in form ation ofimportance for s ignature-extension techniques in com-pute r -a ided c l a s s i fi ca t ion schemes could be ob ta ined .

The aircraf t ins t rum enta t ion cons is ted of an up wa rd-po in t ing i r ra d i a nc e m e te r a nd a dow nwa r d -po i n t i ngradiomete r . In this ins trument , s i l icon diode detectorswere f i l t e red to ma tch the S I90 sensors and the Land-

sat -1 mul t ispectra l scanner bands .A video camera monitored the f l ight t rack so thattargets actua l ly measured cou ld be verif ied in real time .At low a l t i tude , which minimizes e f fec t s of the at -m os phe r ic p a t h , th e a ircraf t radiance N a is

whe r e / = 2-nlL^ m = 2ir /L , and n = 2ir /L z def inethe wa ve num b e r s of wave lengths L^ L^ and L^

respect ively, that can be measured from satel l i te photo-graphs . In the presence of "cloud streets," Lx is the

spacing between th e centers of two consecut ive cloudsin a single street, L is twice the spacing between theaxes of two streets, and L z is twice th e t h i ckness of theconvect ive layer .

Several different cel l types were s tudied by means ofa method in which num er ica l t echniques were used ,

T Va

(6-12)

whe r e p is reflectance, / / i s i rradianc e, and Lamber t i anreflection is assumed. Satel l i te radiance A^ can beequated to the sum of two effects : the path radiance N p ,and a t e rm propor t iona l to sur face re f l ec tance by the




3500 r

3000-

2500-

3 4 5 6 7W indspeed, m/sec

F I G U R E 6-37.—Comparison of a c t u a l wi n d p ro f i l e with ca lcula ted profi les corresponding to cell types 2 t h ro u g h 6.

product of total i r radiance and atmospher ic transmit-

tance T.

N = N +s p

(6-13)

The FOV of the instrument is 2 .6°; therefore, at a300-m al t i tude, the ground resolution is 13 m. The o ut-put w as recorded on an airbo rne char t recorder and latersampled at 20-m intervals . Cal ibrat ion was performedin a l abora to ry us ing Nat iona l Bureau of Standardst raceable standards. Ratios of radiance to ir radiancewere calculated f rom these values fo r areas that could

be related to satel l i te pixels . Skyla b S190A pho tograph swere scanned w i t h a d ig i ta l mic rodens i tometer . Dens i tywas cal ibrated by a compar ison of measured dup l ica tedensit ies produced by the same exposures appl ied to the

original film. After suitable conversion f rom digital

satellite counts to diffuse density and relat ive exposure,an equ ivalent radiance N was computed f rom the rela-tion

N =irtT

(6-14)

where E is absolute exposure; F is the camera lens f-n u m b er ; t is integrated exposure t ime; and T is totalt r ansmi t tance of lens, fil ters, and w i n d o w .

Thus , by measur ing Skylab data for N s and us ing th elow-al t i tude ref lec tance measurements for p for at leastthree dif ferent ground ref lec tors , est imates of N and Tcan be derived and used fo r cor rec t ing a tmospher iceffects. A t satel l i te al t i tudes, total i r radian ce is assumedto be tha t of so lar inpu t .




In a p l o t of N s as a f u n c t i o n of p , the i n t e r c e p t on therad ian ce axis g ives N p , wh ereas th e s lope is p r o p o r t i o n a lto b e a m t r a n s m i t t a n c e an d i r r a d i a n c e . W h e n th e co r r ec t

v a lu es are k n o w n , n ew rad iance values can be co r r ec ted

an d ad ju s ted to ea r l ie r r ad ian ces d e r iv ed f ro m scen e

classes of the same ref lectance.

In a S k y l a b E R E P i n v e s t i g a t i o n ( re f . 6 - 48 ) , a m e t h o dd e v e l o p e d b y Co lwel l ( r e f . 6 -49 ) w as a p p l i e d to the S I 9 2

sensor data to d e te rmin e su r f ace so i l mo is tu r e in thep resen ce of p a r t i a l v eg e ta t io n co v er . Th e r e f lec tan ce of

bare soil decreases fo r in cr eas in g so i l mo is tu r e ( f ig .

6-38). Th e d i f f e r en ce in r e f lec tan ce be tween wet anddry so ils is greater in the ref lect ive i n f r a red th an in th e

v is ib l e p a r t of the sp ec t ru m. Also , as the a m o u n t ofgreen vegetat ion cover increases , th e n ear - in f r a r ed (0 .7

to 1.1 /o im) ref lectanc e increases but red r e f lec tan ce

decreases becau se o f ch lo ro p h yl l abso rp t io n . I f so i l

mo is tu r e is to be in f e r r ed f ro m a field w i t h p ar t i a l

vegetat ion cover , some means fo r r e m o v i n g th e ef f ec ts

of vegetat ion cover ind epe nde nt of the ef fects of var ia -b le so il mois ture is needed. F o r t u n a t e l y , th e n ear - in -

f rared / red ref lectance ra t io is mo re sen s i t iv e to thea m o u n t of v eg e ta t io n co v er th an is either of the s ingle

b a n d s . In ad d i t io n , the r a t io is in sen s i t iv e to soil

mo is tu r e . F ig u re 6 -39 su mmar izes th e imp o r tan t r e la -

t i o n s h i p th a t su g g es ts th e meth o d wi l l w o r k t o n o r m a l -

iz e th e effects of bo th so i l typ e an d so il mois ture. From

these trends , an a lg o r i th m w as d ev e lo p ed in the f o rm

30 r,

2Soil moisture = A' - B'p ± C'p +

ir ir p,.

(6-15)

26

22

20

1000 nm

9 0 0 n m

12 16

Soil moisture, percent

20 2 4

FIGURE 6-38.—Percent r e f l e c t a nce for bare soil as a func t i on of

percent soil moisture at various wavelengths.

w h e r e A, B', C', D', and £" are constants; pjr is in-

frared ref lectance; and pr is red ref lectance. The p /r2

term is a correction for the n o n l in ea r i ty of the effects of

both so il mois ture and vegetat ion , and the (p ir /p r)2

term is a correction for the n o n l in ea r i ty of the r e la t io n -

sh ip be tween p er cen t co v er and the inf rared / red ref lec-

tance ra t io .

A specif ic rela t ion w as f o rmed a f te r s imu la t in g th eref lectance of canopies with 30 c o m b i n a t i o n s of soil

mo is tu r e and vegetat ion cover a nd af te r f in d in g th e

standard least squares regression relation. The specif ic

equ a t io n became

Soil moisture = 19.79 - 0.02p - 0.066pir ir

Pir IP.+ 5 . 0 6 — - 0.067'

lr (6-16)




B

E

g

8

8

S o i l moisture, percent V e g e t a t i o n cover, p e r c e n t

S o i l mois ture , percent V e g e t a t i o n cover, percent

F IGUR E 6 -39 .—The relationships f rom which th e soil moisture algorithm w as developed.

The correlat ion index R 2 of 0.95 for the values usedin this algor i thm indicates th e effectiveness of thea lgor i thm in correcting for the effects of variable

vegetat ion cover and in accurately predic t ing the sur -face soil moisture. Such m odeling can be useful in deter-min ing sensor requirements (spectral bands and signal-

to-noise characteristics) fo r future satel l i te system s inspecific app licat ion s. For ex amp le, the mo deling sug-gests tha t a noise equivalent reflectance difference N E

A p of 0.5 perce nt or more mig ht be required in the near-infrared spectral band for estimating surface soilmoisture in var iab ly vegetated ter rain .

3 1 2 S K Y L A B E R E P I N VE ST IG A TI O N S S U M M A R Y



Th e advantage of a remote -sens ing t echnique for the

de t e r m i na t i on of surface soi l mois ture under variablevege ta t ion -cove r t e r ra in is the abi l i ty to map large areasand to locate homogeneous areas with different surfacesoil m oi s t u r e r eg i m es . W he n t h i s t e c hn i q u e w as a pp l i ed

to ai rc raf t m u l t i s pe c t r a l da ta s imi l a r to the S192 imag-

e r y , posi t ive resul ts were obtained. In figure 6-40, a por -t ion of the test s i te that wa s map ped is sho w n; the m apgives the areal dis t r ib ut io n for soi l mois ture . Tech-n i q u e s us i ng on l y o ne b a nd failed to show cor re l a t ionw i t h soil mois ture . Un der ce r t a in condi t ions , the use of

th e ra t io inf ra red / red re f l ec tanc e , toge the r wi th th escanner the rma l da ta , wi l l i m p r o v e th e s igni f i cance ofth e regress ion equat ion fo r soi l mois ture .

Because of bet ter regis t ra t ion between bands, S I 92conical data w ere used to c ons t r uc t a l and-cover m a p o fan area in southeas tern On tario, Canada. A part ic ularfea ture of this map was t he 10 class if icat ion categoriess hown i n figure 6-41. These classes (water; marsh;

m i x e d c on i f e r / ha rdw ood ; ha r dwood ; s ub u r b a n ; q ua r r yand bare soil ; un differ ent ia ted herbaceo us; and low-,

m e di um - , and high-percent green herbaceous cover) aresuggested as being pert inent to hydrological problemsdealing with runoff , water balance, and water manage-

ment appl i ca t ions . The map was made in two key s teps .Firs t , an unsuperv i sed c lus te r ing a lgor i thm w as used onsix polygon-shaped tes t sites chosen from a ircraf t un-derf l ight imagery 1 day after th e Sky lab pass . Second,th e reflectance ratio /? 10/6 w as used to de t e r m i ne th epercent cover of green vegetat ion. The f inal class if ica-t ion was perform ed us ing 30 s ignatures to define 8classes. W ater w as a lso recognized as a level s l ice fromth e n e a r - i n f r a r e d b a n d . P r o b a b i l i t i e s o f c o r r e c tclass if icat ion were computed us ing a program to gener-a te 1000 points for each s ignature w i th a normal dis-

t r i bu t ion . A best l inear class if icat ion rule was used toobtain correct probabi l i t ies of class if icat ion that weregreater than 90 percent correct for s ix of the eightclasses an d a pp r ox i m a t e l y 77 percent correct for twoclasses, which were suburban and undi f fe rent i a tedvegetat ion. This resul t w as expected because of themixed nature of the class defined.

Com par i son wi th Landsa t recogni tion classes for thesame area showed s imilar resul ts for 75 percent o f thescene. Th e maps were reasonably equivalent in the i r in -

forma t ion content . Mos t of the di f fe rences could be ac-

counted for by differences in training-set signaturesused.

Resolution eements aong scan line

22222222222222222222222222222222222222222222222222222222222222222222222222222777777777766666666<S65555555555l,l.lil.UUW.U333333333322222222221Ull 11111000OOOO9e765<.3ri0987651i 3210987651.321098765U3210987651.3210987651J321098765I.321098765I.3

10.08 percent7 . 7 3 percent

10.16 percent

. .**. .*.. *... , . . . V

*•»*••* ******

•» , .» : : • • • • » • » : . : : . — : •

Symbo

Soil moisture,

percent

O t o 6

6 t o 1 212 t o 1 81 8 t o 2 4

> 2 4

F I G U R E 6-40.—A map of scanner- indicated soi l mois ture (Ontar io,C anada) . Eac h da ta po in t r epres en t s an a r ea app rox imate ly 9 m ( 30ft) on a side. Three sampled soil moisture values are shown for com-par ison.

A n ex tens ive m ode l ing program to use SI92 imageryfo r del ineat ion of o p t i m u m f i s h ing areas in the Gulf of

Mexico was pe r formed by Savas tano (ref. 6-50). De-tailed discuss ion of the model is presented in sect ion 5 .

THE S191 I N F R A R E D SPECTROMETER

Although the S191 Infrared Spectrometer was not animaging device, i t was designed to obtain cri t ica l infor-

mat ion about th e spectra l t ransmiss ion of the a t -

mosphere and about reflect ion characteris t ics of groundclasses of t e r ra in impo r tant to Ea r th resources app l i ca -tions. This knowledge is useful directly in the s tudy ofa t m o s p h e r i c processes a n d i n t h e d e s i g n o fmult ispect ral scanners such as the S192. The search forth e opt imum spec t ra l bands for a g iven appl i ca t ion isone of the major problems in remote-sensing research.




f-r

•: :

* 'I \ f• M \ •*. • '

§$$£f-.cr 4v.

.<??»- A , - i 1.I

W a te r

M a rs h

M ixed con i fer /

hardwoodforest

Hardwoodforest

Suburban

I Quar ry an dbare soil

Undi f ferent iatedherbaceous(e.g., brush )

Low-percent g r e e nherbaceous cover

M edium-percent greenherbaceous cover

High-percent g reenherbaceous cover

0 4Scale, km

•* \ ; * "* -y^x '• N ^ x '\ x-•**.

X.• ^Bowmanville

-- r

Lake Ontar io•

HHH H^ I ^ II HI I

FIGU RE 6-41.—Color-coded S192 recognit ion map of southeas tern O ntar io, C anada. The map was generated from data obtained September1973. The skew apparent in the map results from the use of non-scan-l ine-correc ted data.

The S191, provid ing cont inuous spec t ra over a widerange, was manual ly pointed a t selected targets to ob-tain the spectra l characteris t ics of represented areas onthe surface. Data in two ranges were obtained: between0.4 fj.m in the violet and 2.5 fj.m in the nea r inf ra red ,and between 6.6 and 16.0 /u.m in the t he rma l inf ra red .Scan t ime was 1 second, and the ground area coveragewas appro x im a te ly 500 m in d iamete r .

Data were col lected in s ix spectra l segments acrossthe two ranges (ap pen dix A) ; wi th app ropr ia te reduc-tion and calibration procedures, the data were reduced

to a form sui t ab le fo r ana lys i s . M any Skylab inves t iga -tors used t he s ensor for a tmosp her i c rad ia t ive t rans fe r

exper iments , whereas o the rs found it useful in measur -in g t he sur face rad iance m ore accura te ly .

A n d i n g a nd W a l k e r (ref. 6-51) integrated the ra-diance values from t he two po r t i ons of the t h e r m a l

band on each s ide of the ozone absorpt ion band andrat ioed the values to offset th e effect of a tmospher i c in -fluences on sea-surface tem pera ture m easurements .This t echnique of us ing two the rma l ' bands such asthose avai lable f rom th e S191 Inf rared Spectrometeroffers an a t t rac t ive a l t e rna t ive to cor rec t ing radianceva lues for a tmospher i c t empera tures , mois ture , andaerosol content . Further discuss ion o f A n d i n g andW alker 's inves t iga t ion is f ound in section 5 .

Silva (ref . 6-12) used the output data in the thermalinfrared to compare the data on spectral radiancemeasured by the S191 wi th da ta de r ived f rom surfacemeasurements us ing both a ground sp ec t roradiomete r

and a pyrhe l iom ete r to de te rmine the spec tra l rad ianceand the spec t ra l a tmosp her i c t ransmis s ion . Th e spec t ra lpa th rad iance , a s computed f rom SI91 measurementsand as predic ted by a tmo spher i c m ode l s ( re f . 6 -52) , is




compared in f igure 6-42 for the visibi l i ty con di t ion pres-ent at the test site (Lake Monroe, Indiana) . The tem-p e r a t u r e of the lake was measured, and f igure 6-43shows the compar i son of the spec t ra l rad ianc e de r ivedfrom th e S191 and t h a t due to a black body at the t em-pera ture measured . Agreement of the results w i t h i n ex -

per imenta l e r ror ver if ied both the a tmospher i c mode land th e feasibility of deta i led spaceborne spectrora-diance measurement .

To der ive quant i t a t ive measurements of s t ra to -spheric aerosol characteris t ics , Tingey and Pot ter ( ref .6-53) used S191 data in the 0.4- to 2.5-/Lim band to ac-qu i re high-spectra l -resolut ion data fo r inc rements of 2.4

km of a lt i tude a t t he E a r th l imb. As an in i t ia l s tep, some

s ignal averaging was introduced to improve the s ignal -to -noi se ra t io a t t he low radiance va lue encounte red .Compared w i t h the S192, the S191 proved to be moresensi t ive but less accurate in i ts absolute radiometriccalibration. However, analysis of the SI91 data proved

t ha t aerosol layers could be detected in several spectra lbands a t various a l t i tudes measured from the top of theatmosphere. I t was found that layers a t a l t i tudes of 42,5 0, and 55 km are more r e s pons i ve to l onge rwav elengths , whereas lay ers a t 59 and 66 km were m orerespons ive to wave leng ths nea r 0 .53 f im. Kn owledge ofthe dis t r ibut ion of aerosols is of interes t in as tronomy,meteorology, air -qual i ty surveys , and remote sensing.

In geology , Vincen t et al . (ref. 6-18) applied S191 datato the prob lem of d i f f e r en t ia t in g basal t ic rocks fromdac i te . A tmosph er i c m ode l s f rom An ding e t a l . ( re f.

— R adiometr ic data obtained by S191

— E quivalent radiat ion of black body

Predicted (v isibi l i ty of 24 km and backg round albedo of 0 .04 )

Computed (visibility of 24 km and background albedo of 0 . 3 2 )

_ 4

E±

a 2

- 1

.5 .7 .8

W a v e le n g t h , ^m

1.0

lOOOr

E •

o

1600

400

1 200

9 1 0 1 1 1 2

W ave leng th , ^m

13 14 15 16

FIG U RE 6-42.—Comparison of comp uted and predic ted path ra-diance.

F I G U R E 6-43.—Comparison of r ad ianc e meas ured by S191 over

Lake M onroe , I nd iana ( June 10 ,1973) , w i t h eq u iva l en t r ad ianc e fo ra 297.7-K (24.5° C) black body.

6-54) and radiance data at Yuc c a Flat, Nevada , were

used to calcula te th e average spectra l radiance at thesurface . To com pute spectra l emiss ivi t ies for basalt anddaci te , correct ions for the dif ferent t empera tures of thetwo materia ls were made. The ra t ios of the twoemiss ivi t ies were calcula ted by averaging emis s iv i ty inth e shor t -wave length band and d i v i d i ng by the averageemiss ivi ty in the long-wave length band. This calcu la-

tion w as accompl i shed fo r dif ferent b a ndwi d t h s p r o -posed for fu tu re space sensors; in each case, howe ve r ,t he e m i s s i v i t y r a t i o s f o r b a s a l t a nd da c i t e we r edifferent , an ind ica t ion tha t th e mater ia l s could be sepa-ra ted by means of ra t io techniqu es operat ing in the ther-mal-infrared bands .

In oceanog raphy, M aul et a l . ( ref . 6-16) used the S191nadir data to develop methods for recovering the oceancolor spectrum through the atmosphere. These results

val idated measurem ents for wa veleng ths greater than0.5 j im. More data on marine aerosol propert ies are

needed before a qua nt i ta t ive determ inat ion of the oceancolor spectrum from spacecraft a l t i tudes can be made.

M I C R O W A V E SENSORS

The Skylab ER EP ins t ruments grea t ly expanded themicro wav e remote-sensing program from space by in-c luding both ac t ive and pas sive microwav e ins t rumentsfo r measur ing th e scattering and emi t t ing prop er t ie s o fthe Ea rth ' s surface. The S193 ins tru m ent op erated a t afrequency of 13.9 G Hz both as an a l t imete r and as a




comb ina t ion r ad iom e te r / sca t t e rome te r . The l a t t e r i n -

s t r u m e n t w as designed to prov ide bo th ve r t i ca l andhor i zon ta l po l ar i za t ion da ta at five incidence angles (0 °to 48°) . The S194 radiometer prov ided an a dd i t iona l f re -

quency at 1.4 GHz for gross resolut ion studies of emis-

sion.

Th e a l t ime te r sensor ut i l ized th e h igh - range - re so l u -t ion capabi l i ty of r adar to measure th e su r face he igh tvar i a t i ons a l ong th e sa t e l li t e g round t rack . T h e p r i m a r y

object ive of the a l t i m e t e r e x p e r i m e n t was to establ ish

it s p o t e n t i a l as a r e m o t e sensor of bo th th e geoid overth e ocean and the t opography ove r l and .

T h e b a c k s c a tt e r e x p e r i m e n t p r o v i d e d i n f o r m a t i o n toradar designers concerning th e range of backsca t t e r

coeff ic ients expected from space for a va r ie ty of sur-faces, angles of i nc idence , po l ar i za t ions , and geometr ic

conf igura t ions . Also invest igated was the dependenceof the backsca t t e r on the geome t r ica l c harac t e r i s t ic s andth e p h y s i c a l state of l and areas and on the su r face

roughness over the oceans.S imi la r ly , i t was of in terest to de te rmine th e r ange of

br igh tness t empe ra tu re s t ha t cou l d be expected fo rd i f f e r en t p o l a r i z a t i o n s and incidence angles as sensed

by a r ad iome te r in space. Also to be invest igated werere lat ions be tween th e br igh tness t empe ra tu re a nd t hephys i ca l state of l and areas, th e oceanograph i c su r faceparame te r s , a nd t he a tmosp he r i c v ar i a t i ons . Ove r oceanareas, th e s i m u l ta n e o u s R A D S C A T o b s e r v a t io n s c o u l db e used to prov ide co r rec t ions for the a t m o s p h e r i c a t-t enua t ion of the backsca t t e r measurements.

Several new t e c h n i q u e s and special analysis pro-cedures were developed to conve r t the raw m i c r o w a v e

measurement s t o me an ing fu l da t a fo r i n t e rp re t a t i ona nd c o m p a r is o n w i t h o th e r i n d e p e n d e n t i n f o r m a t i o n .For the al t imeter observat ions, special techniques weredeveloped for (1) the accura t e de t e rmina t ion of the an-t enna po in t ing ang l e f rom th e r adar r e tu rn , (2) theca l ib ra t i on and cor rec t ion of the normal i zed r adar cross

section f o r p u l s e w i d t h / b e a m w i d t h - l i m i t e d c o n d i t i o n s ,(3 ) de te rmin i s t i c and stat i s t ical analysis of the r adarre turn for evaluat ing terrain ref lec t ion character ist ics ,

and (4) the m o d e l i n g of su r face cha rac t e r i s t ic s to reduceint r insic noise of the a l t ime te r he igh t measurement s

and to separate th e height b iases.Tw o approaches we re used for the S 1 9 3 R A D S C A T

data invest igat ions. One was a general invest igat ion inwhich b r igh tness t empe ra tu re an d backsca t t e r we re

categorized for the different incidence angles andpo l ar i za tions t o p rov ide su r face s ig na tu re da t a fo r

fu tu re m i c r o w a v e sensor design. In the second ap -proach , t he mic rowave s igna tu re was co r re l a t ed wi thspecific parame te r s such as ocean windspeed , so i l

moi s tu re , and vegetat ion cover . Using th e second

me thod , i nv es t iga to r s conf ron ted a bas ic p rob l em ofd e t e r m i n i n g th e val idi ty and accuracy o f t he g round-

t r u t h p a r a m e t e r s , an d seve ra l t e chn iques we re used tosepara t e the un ce r t a in ty o f t he g rou nd - t ru th parame te rfrom th e inferred parame te r as measured by t he

mic rowave sensor f r o m space (sec. 5) .The S194 radiometer data obtained over th e oceans

were used p r i m a r i l y to ver i fy th e theore t i ca l r e l a t i ons ofthe m ic rowav e b r igh tness t em pe ra tu re to ocean su r face

v ar iab les such as windspeed , sea - su r face t empe ra tu re ,an d sa l ini ty . Th e d i f fe ren t t e chn iques and analyses usedt o e s t a b l i s h t h e r e l a t i o n s b e t w e e n t h e m e a s u r e dm i c r o w a v e s igna tu re and t he co r re spon d ing phys i ca l

p a r a m e t e r s of the Ear th su r face are discussed in thefo l lowing subsect ions.

The S193 Al t ime te r Expe r imen t

The a l t ime te r p rec i s ion needed fo r geodetic measure-ments over the oceans required a careful analysis of al lp o ten t ia l error sources that contr ibute to the f inal e r ro rin th e geode t i c he igh t de t e rmina t ion . McGoogan et al .

(ref. 6-55) der ived the geod et ic he igh t h g from

h = h hg s a

(6-17)

w h e r e h s is the sate l l i te he ight above a referencesphe ro id as obtained from th e sa te l l i te t r ack ing da t a ; h a

is th e al t i tude measured by the al t ime ter ; and A/ I repre-sents th e dy nam ic ocean e f fec t s due to t ides, winds, andcu r r en ts . As ind i ca t ed by McGoogan, A/I can b e con-sidered negl igib le re lat iv e to the exp ected precision ofa p p r o x i m a t e l y 1 m root mean square ( rms) , a nd no cor-rect ion was made for i t .

Th e major errors are due to orbi tal uncer taint ies anda l t i m e t e r m e a s u r e m e n t i n a c c u r a c i e s . B e c a u s e t h eal t imeter i s used pr imari ly to de termine the higher f re -

quency geo ida l comp onen t s , me thods fo r shor t -a rcanalysis were developed in which systemat ic erroreffects due to ai r drag , thr ust i ng , and geopo tent ial e rrorscou l d be min imize d . Com par i son be tween shor t -a rcanalysis wi th ex t ens ive t r ack ing coverage and l onge r a rc

3 1 6 S K Y L A B E R E P I N V E S T I GA T I O N S S U M M A R Y



-

:

:

J - 3 0

2 2 5

215

2 0 5

195

185

Wfi/Y^fi^^

^ A l t ime t e r res idua lsf rom re f ined

S-band orb i t

G E M - 6 g e o i < K

_ J l_

Alt imeter residuals

from "bad" orbit.

15:25:04 15:25:24 15:25:44 15:26:04 15:26:24

G M T , hr :min :se c

15:26:44 15:27:04 15:27:24

FIGURE 6-44.—Effect of orbi ta l errors illustrated by Skylab altimeter residuals (pass 8, mode 3). A reference geoid, G od d a r d Earth Model 6, is

shown for comparison.

ana lys is w i th reduced t rack ing coverage show ed tha t as ignif icant bias and tilt could be in t roduced by orb i t un-certa int ies (f ig. 6-44). M cGoogan developed techn iquesto es t imate the orbi ta l acc urac y for each pass ; and p o-tent ia l bias values from —20 to 13 5 m, dep end ing onthe q ua l i ty and qua nt i ty of the t rac k ing coverage, wereobtained for dif ferent passes.

Th e er ror sources tha t cont r ibute to the measured

al t imeter height h a were sepa ra ted in to three ma inca tegor ies cor responding to the bas ic ins t ru m ent de l ays ,

th e po in t ing e r ror , a nd t he a t m os phe r i c pa t h de l ay . T h eb a s i c i n s t r um e n t e r r o r s we r e r e duc e d b y c a r e f u l

pref l ight and in- f l ight ca l ib ra t ion of the system delaysand by use of range - t racker design inform at ion .

To de te rmine th e po int ing angle, two new t echniqueswere deve loped . In one t ech nique , the rada r re turn was

used direc t ly for po int ing-a ngle analys is . Because thea l t ime te r operated in essent ia l ly a b e a m wi d t h - l i m i t e dcond i t ion , the mean rada r re turn wave form cons is t ed ofa s t re tched pul se hav ing a t ra i l ing edge that corre-sponded to the angula r va r i a t ion of the antenna ga in .W he n t he an t e nna po i n t e d off - na d i r , the increase of theantenna ga in in the off-nadir direct ion increased thea m p l i t u d e of the t ra i l ing edge rela t ive to the peak

amp l i tude . A p l o t of the theoret ical re la t ion fo r var iousoff - na d i r point ing angles f is s h o w n in f igure 6-45(a) ,and a p lo t of a measured waveform i s shown in figure

6-45(b) . The p oin t ing angle could be measured f rom the




1.0 r

la) T i m e , n s e c

1 n

FIG U R E 6 -45 .—Effec t of point ing-angle varia t ions on radar re turns normal ized to u n i t y , (a ) "Flat sea" return for no j i t ter . Height is 435 km(235 n . mi . ) , (b ) Com parison of measured mean return and theoret ica l re turn for a K id - n an o s ec o n d t ransm it ted pulsew idth (point ing angle 0.5°off-nadir) . Error bars are based on one standard devia t ion a.

deviat ion of the t ra i l ing edge wi th an unce r t a in ty o f±0.05°.

Th e waveform me thod can be used o n l y w h e n th eoff - na d i r pointing angle is less than one-hal f a beam-width (0 .6°) ; beyond this angle , th e accuracy of themethod is degraded because th e l eading edge starts tospread out . Fo r l arger off -nadir angles, th e stat i s t icalcharacter ist ics of the range-t racker "jitter" ( range fluc-

t ua t ions) we re ana l yzed to deduce th e po in t ing ang le .Range j i t t e r is produced by the in t r insic noise of ther adar r e tu rn due to the elect romagnet ic ref lec t ion prop-

erties of the ocean surface . A n e x a m p l e of this tech-n ique i s show n in Figure 6-46. As ment ioned previously ,th e l eading edge stretches out as the off - na d i r angle in -creases above 0.6°. The r ange - t r acke r - j i t t e r ampl i t ude

and f requency response is re lated to the slope of ther i se t ime, and increasing th e r i se t ime wi l l increase th erange-t racker j i t te r and r educe th e b a n d w i d t h , as indi -

cated in figure 6-46(c).

After t he o f f -nad i r po in t ing ang le was de t e rmined ,pref l ight cal ibrat ion data were used t o conve r t po in t ing -

angle offse t to effect ive he ight correct ions. The correc-t ions and ca l ib ra t i on of the data reduced th e absoluterms height e rror f ro m 20 to 10 m; ho wev er , re lat ive er-rors for any given pass sh ould be less than 1 m.

The corrected al t imeter geoid he ight data were plot -ted for all ope ra t ing passes and compared wi th areference geoid (Goddard Earth Model 6 ( G E M - 6 ) ) andw i t h ocean -bot tom topogra phy w he re ava i l ab l e . Severa linterest ing re lat ionships be tween th e measured geoid

and the sea t renches and mounta ins we re d i scove red .(See sec. 5, ent i t led "Oceans and Atmosphere.")

M o u r a d et al . (re f. 6-56) used the cal ibrated al t imeterdata f rom four passes to fur ther invest igate th e effects

of th e orb i t and inst rument noise on the results. A"best

estimate" of the geoidal profi le along th e sate l l i teg round t rack was ob t a ined by app l y ing t he gene ra l izedleast squares col locat ion me thod (GLSC M ) to the




1 .0 r

E s t i m a t e d la c o n f i d e n c e b o u n d s

E R E P p a s s 9

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200

T i m e , n s e c


a l t imete r he ight obse rva t ions . The ana lys i s cons i s t edbasical ly of three steps.

1. The geoidal height was obtained as before (eq.(6-17)) by sub t rac t ing the measured a l t imete r he ightfrom the computed satel l i te height rela t ive to areference spheroid. This res idual was then modeled asthe sum of the expec ted ran dom he ight s igna l and thein t r insic random range noise of the a l t imete r . Fo r shor tarcs (<450 k m ) , th e s ignal can be expressed as the sumof a ca l ib ra t ion cons tan t re f l ec t ing th e sys temat i c orb i t ,a l t imete r an d envi ronmenta l e r rors , and the r a n d o mhe igh t s igna l having va r i a t ions bounded by the ex -pec ted f requency cha rac te r i s t i cs of the global geoidalheight dis t r ibut ions .

2. Using the s ignal spectra l characteris t ics , the in-t r insic range noise was reduced by ap p ly in g t he GLSCMto the res idual values (f i l ter ing).

3. The fi l tered res iduals were then compared withthe Marsh-Vincent (M-V) geoid (Goddard geoid 73

(GG-73) ) , and by us ing weight ing func t ions tha t cor re -sponded to the reduced noise level of the a l t imete r

measurements and the unc e r t a i n t y of the M-V geoid,the GLSC M was reappl i ed to de te rmine a ca l ib ra t ionconstant and the geoidal heigh t deviat ions rela t ive tothe ground- t ru th M-V geoid . Severa l segments of theshor t -a rc t racks were combined in the GLSC M solu t ionby con stra ining the adja cent geoidal height values of the

segments to be equal .The values of the cal ib rat ion constant reflect ing po-

tent ia l a l t imeter and orbi ta l biases varied between 20and 50 m for passes 4 and 7 and compared wi th es t i -mated orbi ta l biases of 20 to 30 m (ref. 6-55) for the

same passes.

Ground t ru th , cons i s t ing of the free-air gravi tyanomal ies , th e b o t t om t opog r a phy , and the re fe renceM-V geoid a long the Skylab gr ound t r a c k , wa s assem-

bled and compared wi th the de r ived geoid prof i l e . Anexam ple of the resul ts is show n in f igure 6-47. The




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1111:40 1 2 3

Frequency, H z

FIGURE 6-46.—Off-nadir p oint ing-a ngle effec ts on range an d power spect rum, (a ) S k y l a b 4 pass 38/86; ( = 0.6°. (b ) Skylab 2 pass 9;f - 1.1°. (c)Skylab 3 pass 21/32; f = 1.4°.




I

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14:32:00 14:32:30 14:33:00 14:33:30 14:34:00 14:34:30

G M T , h r : m i n : s e c

F IGUR E 6-47.—Geoid undula t ions c omputed from S k y l a b a l t imet ry data (pass 7 , m o d e 5) .

1 - 4 . 514:35:00

re la t ive ly large an d s lo w f r equ en cy f lu c tu a t io n s of the

unf i l tered a l t imeter geoid we re caused by a large off -

nadir angle (1 .25°; ref . 6-55). The applicat ion of the

GLS CM ef f ec t iv e ly suppresses these noise f l u c t u a t i o n s ,

as seen by the resu l tan t f i l tered a l t imeter geoid . The

depression of the al t imeter geoid is d isp laced h o r izo n -

tally by a p p r o x i m a t e l y 200 km r e la t iv e to the ground-

tru th geoid (GG-73) bu t agrees w i t h th e locations of thePu er to Rico Tren ch an d th e f r ee -a i r g r av i ty an o m aly .

Other results o f Mo u rad ' s an a lys i s th a t i l lu s t r a te th ea l t imete r sen s i t iv i ty to the fine s t ru c tu r e of the geoid

are discussed in section 5 .

Th e d e te rmin a t io n of values of the n o rmal ized r ad a rcross section o-° of the ocean at n ear -n ad i r angles and

their accuracy was der ived by Brown (ref . 6-57) f rom

the al t imeter data and ca l ib r a t io n curves. The r ad a r

cross section o-°(i/O is expressed by

w h e r e ij »

ch

L

POMcal

CD S

K (6-18)

is the incidence angle that produces the

p eak am p l i tu d e ; i / /0 = -Jcrp/h

is the speed of l ig h t

is the al t imeter a l t i tude

is the p a t h loss

is the p eak of the mean p o wer as ob-ta ined f rom th e automatic gain contro l

(AGC ) cal ibrat ion curves at receiver

temp era tu r e T r




K

l s t n ei n - f l i g h t r e c e i v e d - p o w e r

measurem ent obtained in the cal ibra-t ion da ta submode (CDS)is the correct ion factor for the changeof measured waveform re l a t ive to thewaveform used in ca l ib ra t ion , and theconvers ion f rom the mean of peakvalues of the received power measuredby th e a l t imete r to the peak of themean va lues needed to c om pu t e <r°

is basical ly the convolut ion of thesys tem poin t - t a rge t response wi t h t heflat sur face impul se response and is afunct ion of the rada r pa ramete rs , th e

a n t e nna pa t t e r n , th e poin t ing angle £ ,and the t ime de lay rp at whi c h m a x -i m u m v a l u e is obtainedrepresents th e sys tem losses obtainedfrom pref l ight ca l ib ra t ion

Brow n ( re f . 6 -57) com puted va lues of <r ° fo r each ofth e passes du r i ng wh i c h th e po int ing angles w ere less

tha n 0.8° . The p oint in g angle was derived fro m thewaveform re turn a s descr ibed previous ly .

Us ing th e po in t ing angle a nd t he measured antennapa t t e rn , the func t ion /could be computed. Because the

a n t e nna pa t t e r n was asymmet r i ca l , two values for /

we r e c om pu t e d , one wi th th e poin t ing angle assumed tobe in the rol l direct ion (£, ) and o ne assigned to the pi tchdirect ion (£ p). Fo r Skylab 2 and 3, the values of Fas afunct ion of £ are s h o w n in f igure 6-48. Typical values of

< r ° ( t j j ) fo r smal l incidence angles ( i / » = 0.5°) varied be-tween 8 and 16 dB.

B r o w n (ref . 6-57) a lso perfo rm ed an error analys is toes tabl ish the uncerta inty of the derived values of <r° as afunct ion of the point ing angle . Est imates of errors dueto uncerta int ies in cal ibra t ion, to F, and to d om inan tbias were made, and the resul tant error w as c o m p u t e d .The Sky lab 2 and 3 resul ts show tha t absolute and rela-tive rm s errors of 0 .7 and 0.3 dB, respect ively, areachieved for a kn ow n pi tch angle of 0° to 0.5° . W hen theantenna pa t tern w as degraded, as in Skylab 4, rms errorsof a pp r ox i m a t e l y 4 and 0.5 dB we r e obtained for ab-solute and rela t ive values , respect ively, with pi tch

angles of 0° to 0.5°.A l t imete r pe r formance over t e r ra in in the Uni tedStates was invest igated by Shapiro et a l . ( ref . 6-58) toeva lua te th e capabi l i ty of the sensor to prof i l e terra in

- 135

-136

- 137

-138

' -139

•"-140

-141

- 1 4 2

- 1 4 3

- 1 4 4

|p = 0°, 4, v a r i a b l e

4 r = 0 °, 4 v a r i a b l e

.2 . 4 .6 .8 1 .0 1 .2 1 .4 1 .6P ointing a n g l e | or4r, deg

FIG U RE 6-48.—Fas * funct ion of ( O ' , f r) an d (^0°) fo r Sky lab 2an d 3.

t opography a long the s a te l l i t e groundt rack . The non-homogene i ty o f t e r ra i n t opog r a p hy w i t h i n a f oo t p r i n t

reduced th e potent i a l he ight accuracy b u t p r ov i de drela t ively rel iable t rackin g over m ost areas ha v i ng s m a l lhe ight va r i a t ions . In general, th e existence of high-ref lect ivi ty pa tches provided a wa ve f o r m on w h i c h th esplit-gate range t racker could opera te . The meanreflected power re l a t ive to the ocean return fo r d i f fe ren t

types of t e r ra in is l isted in table 6-V. Th e va luesdecrease with increasing t e r ra in com plex i ty . The l a rgerece ived pow er a t nadi r over th e salt flats is e q u i va l e n tto a rada r backsca t t e r ing coeff ic ient of 32 dB a nd , whe ncompared with the Moore et a l . ( ref . 6-59) value of 14dB a t 1.5° incidence angle , indicates a high ly specularre turn . Genera l ly , a dom inant specula r re turn provid ed

th e requi red waveform fo r proper range-t racker opera-t ion as s hown b o t h by t he d r opof f of the backsca t t e rb e t we e n 0 ° ( a l t i m e t e r ope r a t i on ) a nd 1 . 5 ° ( s c a t -terometer operat ion) over the same type of terra in, andby th e waveform ana lys i s . In figure 6-49, a typ ica l ex -a m p l e of the rada r re turn waveform f rom fa rmland inIowa is c om pa r e d w i t h th e water re turn waveform f romL a k e M i c h i ga n . Th e t e r ra in re tu rn is s imi l a r to a po i n t -target r e t u r n w i t h a sharp t ra i l ing edge, whereas th et ra i l ing edge of the L a k e M i c h i ga n r e t u r n is s tretched byth e diffuse r e t u r n of the water sur face . A l so shown isth e correla t ion between th e t e m por a l ( e q u i va l e n t to a

spatia l resolut ion of 70 m) ampl i tude va r i a t ions at the

r i s e t i m e p o r t i o n o f t h e i n d i v i d u a l r a d a r r e t u r n s(100/sec). Th e ana lys is shows tha t th e a m p l i t u d e of thewater return decorrela ted for a di sp lacement of 70 malong the t rack , whereas th e l and re turn is correla ted fo r




T A B L E 6- V.—Dynamic Range of Peak Terrain R a d a rReturn Relative to Ocean Return

O W a t er in Lake M ich igan (100 mHz)

n Farmland in Iowa (10 mHz)

7Y/>c of terrain Radar return. JK

Salt flats

L ake s

Ocean, des er t sValleys , p la i ns , c i t ie s , s w am p s

Ridges , canyons , d ry lakes

Hills, r ange s , m ount a i ns

Cliffs, fores t

2010

0-5

-10

-12

-16

several hundred meter s . T h u s , i t can be deduced t ha tspecular patches of a p p r o x i m a t e l y a few h u n d r e dmeters exist and t h a t th e al t imeter measures th e he igh tto these br igh t spo ts w i t h i n th e a l t ime te r foo tp r in t .

F i g u r e 6-50 s h o w s a n a l t i m e t e r o u t p u t a n d

t opograph i c map p rof i l e . An exampl e o f t he a l t ime te rprof i l e over Arizona is shown in f igure 6-50(b) com-

pared wi th th e power r e tu rn (fig.6-50(a)) and anequ ivalent topograph ic p rof i le (f ig . 6-50(c)) obtainedfrom a 1:250 000-scale contour map. Th e largerece ived -power var i a t i ons cou l d not be corre lateddirect ly wi th t he t opograph i c var i a t i ons because t hey

also depend s ign i f i ca n t ly on surface roughness, soi l

t ype , a nd soil mois tu re . Add i t i ona l var i a t i ons a recaused by i n s t rum enta l e f fec ts of the n a r r o w A G C sam-

p l in g gate.

Th e corre lat ion between th e al t imeter prof i le and themap prof i l e shown in f igure 6-51 (a) gives a c orre latio n

coefficient of 0.92 w h e n th e al t imeter prof i le is shif tedby app roxim ate l y 7 km b ackw ards re l a t i ve t o the m approf i le . A corresponding mean height di fference of ap-p r o x i m a t e l y — 15m and an rms height var ia t ion of ±35m were comp uted, a nd the resul ts are show n in f igure

6-51 (b). The b a c k w a r d sh if t has been detected in allpasses and is p r o b a b l y due to the i ne r t i a l response ofth e range t racker to he igh t var i a t i ons .

Th e resul ts show that an al t imeter , such as the SI93 ,

prof i les t he subsa t e l l i t e g round t rack topograph y bu tacts as a low-pass filter (as opposed to al t imeter geoidaloperat ion over th e ocean) because it responds p r i m a r i l y

to the lower specular areas w i t h i n t h e f o o t p r i n t . F u t u r e

al t imeters should provide for both specular and di ffuser e t u r n s a n d shou l d have ad d i t i ona l sam pl ing ga te s

avai lable so that th e ver t ical s t ruc ture w i t h i n a foo tp r in tcan be de te rmined .

-.

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1 2 3 4 5 6 7 8 1 2 3 4 5 6 7

G ate position

0 W a t er in L a k e M ichigan (100 mHzl

n Fa r m la n d in Iowa (10 mHz)

140 210

D isplacement, m

F I G U R E 6-49 .—Compari son of t e r r a i n w ave form s ob t a ine d on

S ky lab 3 pass 17. (a) Radar re turn, (b ) Aut ocor re la t i on .

The S193R A D S C A T a nd S194 Radiometer

E x p e r i m en t s

A n overal l evaluat ion of the R A D S C A T m e a s u r e -ment s w as m a d e by Moore et al . (ref. 6-59) to de te rmine

th e r e l a t i onsh ips of the measurement parame te r s to

D A T A A N A L Y S I S T E C HN I Q U E S 3 2 3



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204 206 208 210 212 214 216 218 220 222 224 226 228

31 .94°N D a t a b l o c k (pass 1 6 ) 33.04°N1 1 3 . 8 1 ° W 112.40" W

(c )

F I G U R E 6-50.—Skylab alt imeter output an d topographic m ap prof i le fo r Ar i zona test s i te, (a ) Alt imeter power re t u rn , (b ) Alt imeter p rof i le ,

(c) Topographic p ro f i le t rans lated for ma xim um cross corre lat ion wi th radar he igh t .

po l ar i za t ion , incidence angle , soi l mois ture , type of ter-ra in, and vegetat ion cover. Data obtained over th eUni ted S ta tes , Brazil , and the oceans were categorized,

and specific test areas in which large anomal ies were ob-served were used to es tabl ish potent ia l correla t ion withth e phys ica l pa ramete rs of the observed areas.

The ang ula r dependence (app rox im a te ly 1.5 ° to 52°

fo r th e S193 radiometer) of the br ightnes s t empera ture

Tro v e r th e cont inental United States is summar ized inf ig u re 6 -5 2 ( a ) fo r v e r t i c a l - t r a n s m i t / v e r t i c a l - r e c e i v e( V V ) antenna polarizat ion. Also shown is the num b e rof samples fo r each data point and the u p p e r and lowerdecile values. The mean brightness temperature overland is a pp r ox i m a t e l y c ons t an t at 268 K wi t h a deci le

3 2 4 S K Y L A B E R E P I N V E ST I GA T I O N S S U M M A R Y



i. o r

•

70r

1 0- 9 . 5 - 7 . 6 - 5 . 7 - 3 . 8 - 1 . 9 0 1 . 9 3 . 8 5 . 7 7 . 6 9 . 5 1 1 . 4 1 3 . 3 1 5 . 2

( b ) D i s p l a c e m e n t , k m

F I G U R E 6 -5 1 .—Mean and s tand ard deviat ion of he igh t d i f fe rence

an d cross corre lat ion of a l t i m e t ry g round h e i gh t as a func t i on of map

e levat ion (Skylab 3 pass 16, data blocks 204 to 228). (a ) Corre lat ionbe tween al t imeter p ro f i le and map pr of i le , (b) Mean he igh t

d i f f e r en c e .

value range of ap pro xim ate ly ±15 K for al l inc idenceangles. This re lat ionship agrees with a Lambert ' s law

model fo r very rough surfaces.The mean backscat ter r esponse over land shown in

f igure 6-52(b) reveals a two-step dropoff wi th inc idenceang l e 9 ; t h i s r e l a t i onsh ip can be ana l y t i ca l l y expressedby a best fit to the data by

o°(0) = 1.7e-(e/5

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for 0° < Q < 11°

o°(6) = OAe ( f l / 2 9 - 6 0 ) for 11 ° < 6 < 45 °

(6-19)

.

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1000

500

0

No . o f samples for each data point

i L i 1 1 1 1 , 1 1 1 1 1 1 1 1 1 . , iO Mean

n Upper decile290

28 0

27 0

26 0

250

24 0

V Lower decile

S-, DDnn nnnD o°u u

- O °O °5 3 o° o ° o o o v oo°ooo o o

V "7

"r^7

^ ^7 V? V V <-? ^ <\7- V 7 y ^

t i i i i i i i i i

( a )

lUUUr-

500 \-nl-ili

1 0 1 5 20 2 5 3 0 3 5 4 0 4 5

I n c i d e n c e a n g l e , d e g

No. of samples for each data point

50

L

15

S 10

C

— c

-10

-15

(b)

1 0 1 5 2 0 2 5 3 0 3 5

I n c i d e n c e a n g l e , d e g

40 45 50

FIGUR E 6-52.—Summary of an gul ar dependence of br igh tness tem-

p e ra t u re and bac ks c a t t e r fo r V V an t e nna p o la r i za ti on d ur i n g S ky lab

2 and 3. (a) Angula r r ad i om e t r i c response f rom S193 radiometer

operat ions , (b ) Angula r s ca t t e rom e t r i c response from S193 sca t-t e rometer opera t ions .

Th e decile values around th e m ea n val ue a re re lat ive lysmal l (=4 dB) for angles larger than 10° because ofspat ial averaging of the large f o o t p r i n t (>100k m 2 ) .

The angular dependence of the brightness tem-

pe ra tu re over the oceans for both ver t ical and horizon -

ta l polar izat ions agrees with a sl igh t ly rough surfacemodel , whereas th e mean backsca t t e r ocean response




fo l lows a one-step dropoff given by

= 16 e

fo r VV po l ar i za t ion and

(6-20a)

(6-20b)

f o r h o r i z o n t a l - t r a n s m i t / h o r i z o n t a l - r e c e i v e ( H H )

po l ar i za t ion , whe re 0° < 9 < 45°.Stat i s t ical analysis of the d i f fe ren t measurement

param eters over land showed a low corre lat ion betweenthe b r igh tness t empe ra tu re and t he backsca t t e r coeffi-

c i en t and a h igh co r re l a t i on be tween h or i zon ta l and ve r -

t ica l po l ar i za t ion as we l l as be tween t he mic rowave

backsca t t e r measurement s a t d i f f e ren t i nc iden t ang le sfo r 9 > 15°. These resul ts i m p l y (1 ) that ac t ive andpass ive mic rowave measurements over te rrain a re sen-s i t i ve t o d i f fe ren t su r face and /o r a tmosphe r i c charac -t e ri s ti c s , w he reas t he use o f m ul t i p l e po l a r i za t ion , a tleast for the given spat ial resolut ion, i s redundant , and(2 ) t ha t s i de - l ook ing radar pe r fo rma nce can accoun t fo r

th e far-range effects.Th e backscat ter coeff ic ients a re compared to l and

use categories for di fferent incidence angles in f igure6-53. The <r° values ov erlap for mos t lan d use catego-r ies , except for the high values over th e sal t f lats inUtah , wate r su r face s at an incidence angle of 1.5°, and

the low w ater values at inciden ce angles of 33° and 46°.A n a t t e m p t to dist inguish di fferent types of te rrain b y astat i s t ical decision procedure appl ied to the m i c r o w a v edata w as unsuccessful for two reasons. Th e larger scat-t e rome te r foo tp r in t gene ra ll y i nc l uded d i f fe ren t landuse categories; and other fac tors , such as soi l moisture ,m a y d o m i n a t e th e microwave t e r ra in response.

To establish a more precise corresponden ce betweenth e p h y s i c a l state of the t e r r a in and the m i c r o w a v e d a t a ,some u n i f o r m l a nd areas ove r w hich l a rge dev ia t ions inth e microwave data were observed were studied indetail . A un i fo rm range l and g round t rack in Texasshowed a large change in brightness temperature (288 to

23 6 K) and backscat ter s ignal ( -11 to -7 d B ) . Tode te rmine whe the r t h i s change cou l d be r e l a t ed to so i lmoisture, t h e p a t t e r n o f p r e c i p i t a t i o n a l o n g t h eground t rack for 5 days preceding th e overpass and on

the d ay of the overpass w as studied. Using th e 5-day an-t e ceden t p rec ip i t a t i on index (AP I ) as an e s t imate o f t he

soil m o i s t u r e d i s t r i b u t i o n a l o n g t h e s a t e l l i t eg round t rack , a co r re la t i on be tween t he mic rowav e da t aand t he soi l moisture w as c o m p u t e d . T h e resul t indi -cated a re la t ive ly h igh co r re l a t i on (—0.7 6 fo r l and emis -

sion and 0 .62 for backscat ter) . Resul ts by Eagleman e tal . ( ref . 6-60) show that the corre lat ion is imp rov ed if

the API est imate of soi l moisture is extended over 10days .

An othe r area in wh ich large changes in bac ksc at terand emission w ere observed was the Great Salt L a k eDeser t in U tah . Br igh tness changes of a p p r o x i m a t e l y 70K be tween th e s u r r o u n d i n g t e r ra i n and t he deser t wereobserved by the SI93 sensor at a f requency of 13 .9 GHz(fig. 6-54), by the S I 9 4 sensor at 1.4 GHz (f ig . 6-55) , andby t he Nimb us-5 r ad iom e te r a t 19 .35 GHz. The N im-bus-5 spacecraf t had passed over the area many t imes in1972 and 1973. Corresponding large anomal ies in back -

scat ter are indicated in f igure 6-53. To e xp lain this largechange in emission and ba cksca t t e r over an appar en t l yd ry and smooth region, a two-layer surface model was

assumed in whic h the l ow emiss ion and t he large back -scat ter could be assoc iated w i t h a subsur face b r ine laye rhaving a die lec t r ic constant considerably larger thanthat of the surrounding area. This model was based onthe h i s to ry o f t he r eg ion , which was origina l ly coveredby L ake Bonnev i l l e . The measurements i nd i ca t ed t ha tth e t h i c k n e s s of the dry surface layer m ay vary from 1

m to 10 cm over th e Great Sal t Lake Deser t .

The l a rge un i fo rm fo re s t and savanna- type a reas i nBrazil provided an opportuni ty to invest igate the effect

o f differen t b iomes on m ic rowave rad i a t i on and sca t t er .Th e SI93 backsca t t e r pa t t e rn de l inea t ed th e b o u n d a r ybetween th e re l a t i ve l y w et rain forests and t he d r y e rsavanna an d thornbush region. A pseudoimage sig-na tu re o f t he r eg ion ob ta ined a t VV and HH an tennap o la r iz a t io n s i s sho wn in f igure 6-56. These detai led in-vest igat ions have demonstrated that soi l moisture i s themost signif icant inf luence in te rrain microwave emis-sion and backscat ter and that soi l moisture may maskth e roughness features of the observed terrain .

The SI94 radiometer observat ions over water sur-

faces were evalua ted by Hol l inge r and Lerne r ( ref . 6-61)to d e t e r m i n e th e response of the r ad iome te r to var ious

oceanograph i c parame te r s . A r igorous and sys t emat i cme thod w as developed to c o m p u t e th e expected anten-n a t empera tu re a n d compare it w i t h th e measuredvalues.




20 r

CO 15•o

~ 10

CQ .5

I I I I I I I I I I IA D l D 2 F R S F S H T F W

(a) Categories

15

m 10•o

"c•— 5

"Q J-

E1

°da

S -5O

*m

- 1 0

. i i i i i i i i i i i iA D l D 2 F R S F

(b ) Categories

i i i i i i iS H T F W

0

CO

I- -50

' (_>

1"10

1-15•22

O

f"2°OQ

- 2 5

- 5

CO

3 - - 1 0^ . ... OJ

— — ^^,"3 -^^

o

— en

~ -20OJ

"rotj

«- 25OJCD

1 1 1 1 1 1 1 1 1 1 1 1 1 1 t 1 1 1 1

_ _—

—. _ _ - i ^^

....

....-

i i i i i i iA Dl D2 F R SF SH TF W A Dl D2 F R SF SH TF W

( c) C a t e g o r i e s ( d) C a t e g o r i e s

— Mean

— Upper standard deviation

•—Lower s t a n d a r d deviation

A Agr icu l tu reD l Desert (Nevada and Arizona)D 2 D e s e r t ( N e w Mexico a n d T e x a s )

F North A m e r i c a n f o r e s tR Rangeland

S F S a l t f lats, Utah

S H S a n d h i l l s , N e b r a s k a

T F Tropical forest, South AmericaW W ater, ocean

F I G U R E 6-53.—Comparison o f b ac k s c a t t e r in g coeff ic ient f o r v a r io u s terrain c a teg o r i e s a t f o u r i n c iden c e an g le s f rom S k y l a b 2 and 3 data o b -

t a in ed u s in g the S193 s c a t t e r o m e t e r and VV a n t e n n a po la r i z a t io n , (a) 8 = 1.5°. (b) 6 = 17°. (c) 9 = 33°. (d) 9 = 46°.

The an tenna tempera tu re T A was obtained f rom

+ Q Q +t a

U Ut a

V V \ d S lt a )

(6-21)

w h er e K is Bol tzmann ' s cons tan t , êis th e effect ive an -tenna area, / ,, Q r U r and K,are th e Stokes param eters of

th e to ta l r ad ia t ion , / a, Q a, U a, and V a are the Stokes pa-r ameter s of the a n t e n n a p a t t e rn in the proper r ef erencef r ame , and ft is the sol id angle over w h i c h th e in tegra -t ion is p e r f o r m ed .

The use of the Stokes parameters in equation (6-21)permits the cross-polar ized components of the emitted,ref lec ted, and atmo spher ic radia t ion to be s im plys u m m ed and then to in ter ac t d i r ec t ly wi th th e a n t en n apolar izat ion character is t ics . A computer p rogram w as

developed to compute the Stokes parameters as a func-

t ion of the oceanographic and instrumental parametersin several steps.

First, the die lectric cons tant o f seawater w as com-puted as a func tion of radiom eter f requency, sea-surface

temp erature, and sal ini ty . From the computed dielec tr icvalues, th e hor izon ta l and ver t ical Fresnel ref lec t ioncoefficients for water as a func t ion of inc idence anglewere determined. The Fresnel ref lec t ion coeff ic ients




42.00

41.70

41.40

41.10

4 0 . 8 0

-

;--

40.50

40.20

39 .90

39 . 60

39.30

39.00

MudflatsinriYri-iYrm

] Mountains

| ] Sal t f la ts

] G reat Sal t Lake Desert

@— Footprint number

" " B r i g h t n e s s

temperature, K

Study

area

G reat Salt Lake

,• Sal t Lake City

/Utah Lake

Utah

Scale, km

I

115.20 114.60 114.00 113 . 40 112 . 80

Longi tude, deg W

112.20 111.60 111.00

F I G U R E 6-54.—S193 rad iometer (13.9 GHz) footpr int s over th e Gre a t Salt Lake Dese r t , Ut ah ( June 5 , 1973).

were then modi f i ed to accoun t for the surface rough-ness by us ing th e empir ical re lat ion fo r different ialb r igh tness t empe ra tu re

A T = 0.134C/ /B

1 / 2(6-22)

w h e r e U is the windspeed in kno t s and / is the fre-qu en cy in gigaher tz .

Th e Stokes parameters of the emit ted and reflected

componen t s we re t hen ob ta ined by mul t i p l y in g t heprop er combina t ion of hor iz onta l and ver t ical ref lec t ion

coefficients by t he eq u iva l en t b l ack -body rad i a t i on . For

3 2 8 S K Y L A B E R E P 1 N V E S T I G A T I O N S S U M M A R Y



Center of footpr int L lat. 41 .4 5° N , l ong . 115.28"W

Center of footpr int 51 : lat. 3 3 . 6 6 ° N , long. 111.91°W

120 140 160 180 200 2 20 2 40

Distance from center of footprint 1, kin

260 2 80 300 320 340 360

F I G U R E 6-55.—S194 (1.4 GHz) b r i g h t n ess t em pera t u re as a func t i on of d i s t a n ce from th e center of the footpr int over th e Grea t Salt L a k e

Desert, U t a h .

th e emi t t ed component , th e black-body radia t ion is ob-t a ined f rom the Rayle igh-Jean s appro x ima t ion toP lanck ' s b l ack-body radia t ion l aw.

The sky radia t ion needed for the de t e r m i na t i on ofth e reflected component of the Stokes parameters w ass e p a r a t e l y c o m p u t e d f r o m s i m p l i f i e d a t m o s p h e r i cmodels . For this purpose, th e absorpt ion coefficients

fo r oxygen, water vapor, and l iquid water were deter-mined as a funct ion of frequency and then integrated

along th e pa th of propaga t ion to obtain both th e down-ward - l ook ing and the upwa r d - l ook i ng r a d i a t ion . Th eresul tant values were then used to c om pu t e th ereflected and a tmosph er i c S tokes pa ramete r compo-nent s as wel l as the a tmospher i c a t t enua t ion . A f ina l

step in the program t rans formed th e satel l i te coordinatesystem of the antenna pa t t e rn to the coordinate sys tem

of the observed surface so t ha t th e in tegra t ion show n inequat ion (6-21) could be performed.




T h i s segmen t

Second segment, pass 7

3 South Bahia rain forest

11 Thornbush

12 Savanna

- 1 2 d B

F IGUR E 6 - 5 6. —Ps e ud oi m age s p rod uce d from backs ca t t e r response w ith cross t rack-cont iguo us , p i t ch 29° mode of S193 operat ion over Braz i l .




The integrat ion w as made by m a p p i n g th e SI94 an-t enna beam pa t t e rn (9 } dB = 15°) by a grid of 1728point s out to 41° off -nadi r so as to inc lude th e m a j o rside lobes. The he ight , th e l ongi tude , and the la t i tude atnadir were used as re fe rence poin t s fo r each observa-t ion ; then , th e posi t ion w i t h i n th e antenna beam w as

com pute d for every 10° in azi mu th and 0.5° nad ir angleto a m a x i m u m of 18°, and every 2° nadir angle to a max-i m u m of 41°. Fo r m i x e d l a nd and water surfaces, eachpo i n t w as t hen ident i f i ed as be ing on ei ther land orwater and the i npu t s to the models were adjus ted accor-d ing l y . The land radia t ion w as obtained from S194m e a su r e m e n t s w h e n l an d w a s k n o w n to fill the a n t e nnab e a m c om pl e t e l y . A separate program designed to com-pu t e th e c on t r i b u t i on of s ung l i n t as a func t ion of Sunelevat ion angle and windspeed w as used pr imar i ly toe l imina t e extreme data points .

Th e S194 radiom eter measu remen ts w ere cal ib ratedover three areas characterized by calm seas ( w i nds pe e d

U < 2.6 m/sec (5 k no t s ) ) , m i n i m um a t m os phe r i c loss,and avai labi l i ty of ve ry good ground- t ru th da ta (passes9 and 23) . Us ing th i s ca l ib r a t io n , t he computed andmeasured antenna temperatures for a l l data (31 passes)were compared . The mean va lue of the difference is-0.0035 K wi t h a s tandard deviat ion of 1.3 K. Thesma l l re su l t an t e r ror indica ted tha t th e theoret ical re la-

t i ons h i p s between th e br ightnes s t empera ture a ndsa l in i ty , sea-surface t emp era ture , and w indspeed couldbe di rec t ly used to p r e d i c t th e 21-cm radiomete r s en-s i t ivi ty to these pa r a m e t e r s .

Th e evaluat ion of the R A D S C A T pe r f o r m a nc e as awi nd sensor over th e ocean required th e de ve l opm e n t

of new t echniques and model s to provide th e best esti-ma te of the windspeed for a given measured value ofth e normal ized rada r cross section. Al tho ug h previou stheore t i ca l and exper imenta l inves t iga t ions had indi -ca ted tha t th e measured radar cross section is rela ted toth e sea-surface roughness and t h a t th e surface rough-ness in t u r n can be rela ted to the sur face windspeed ,considerable scatter in the da ta prec luded th e es tabl ish-m e n t o f q u a n t i t a t i v e r e l a t i o n s h i p s . T h e S 1 9 3RADSCAT observa t ions provided , for the first t ime , alarge data base, a wide range of wind condi t ions , anddif ferent ins t rumenta l and geomet r i c conf igura t ions(polarizat ion and inc iden ce angles) so t h a t th e m e t hods

of statistical analysis could be ef fec t ive ly used.The basic approach as used by C a r done et al. (ref.

6-62) w as re l a t ive ly s imp le . Th e values of the measured

backscat ter coefficients as a f u n c t io n of posi t ion andt ime were accumulated and compared wi th th e corre-s pond i ng su r face - t ru th windspeed va lues . Th en , us ing at he o r e t i c a l r e l a t i ons h i p b e t we e n b a c k s c a t t e r a n dwindspeed , th e bes t - f i t re l a t ionship be tween the twoparamete rs w as es tabl ished. The i m p l e m e n t a t i o n of t h i s

a pp r oa c h , howe ve r , wa s m uc h more complex . In addi -tion to the a c c um ul a t i on and eva lua t ion of the largea m o u n t of da ta , th e da ta had to be s t ra t i f i ed accordingto quali ty and q uan t i ty , and according to the range ofwi nds pe e d and wi nds pe e d d i r e c t i on , so t ha t moremeaningful and accura te re l a t ionsh ips could be de r ived .

Because th e q ua l i t y of the convent ional sea-surface-t ru th windspeed va lues w as k n o w n to be highly va r i -able , a special effort w as made to i m pr ove th e es t imateof the win d vec tor at a given locat ion and t ime by uti l iz-

in g al l avai la ble data sources as nea r to the locat ion andt i m e of the S kylab pass as poss ible . The win d da ta wereclassified according to qu a l i ty (ob ta ined f rom a i rc ra f t ,

weather ships , t rans ient ships , e tc . ) , and specia l modelswere used depending on the k i n d of weather sys temsand locat ions .

Th e ana lys i s fo r H ur r i c a ne A va il lustrates th e tech-niques used to acqu ire regional windfield data . Begin-n ing w i t h th e l aunch of S k y l a b , a sys tematic search w asm a d e fo r we a t he r d i s t u r b a nc e s ne a r th e S k y l a bground t rack to provide a large range of windspeeds forda ta in te rpre ta t ion . In early June 1973, it was a ppa r e n tthat a tropica l s torm would dev elop in to a hu rrica ne offth e southwes t coast of Mexico and t ha t it would in te r -sect wi t h a S k y l a b pass on J une 6. Prepa ra t ions for ob-taining S193 measurements were m a de , and the s torm

w as t racked by U.S. A ir Force a i rc ra f t . The N a t i ona lO c e a n o g r a p h i c a n d A t m o s p h e r i c A d m i n i s t r a t i o n( N O A A ) aircraft used in supp ort of the Sk ylab observa-t ions w as di spa tched to Acapulco , Mex ico , to flyt h rough the eye of the h u r r i c a n e on J u n e 6, the day ofth e expected Sk ylab pass . Th e m e a su r e m e n t s m a de byth e aircraft (f ig. 6-57) were then used di rec t ly a s inp utb ounda r y cond i t ions to a hu r r i ca ne mode l descr ibed byCardone et al. (ref. 6-62) to derive a first estimate of thes treamline-isotach d i s t r i b u t i on of the wi nd f ield . Themodeled wind field w as t hen re f ined by i n c l ud i ng a ll

ship reports and data from other a ircraf t near th e h u r -r icane. The resu l t an t compos i t e ana lys i s of the surface

w i n d field is shown in figure 6-58. The solid lines(s t reamlines) are paral le l to the wind direct ion, and thed a s h e d l ines ( i so tachs ) a re c o n t o u r s o f c ons t a n t




72.01 1 4 0 161.7( 1 2 0 1

51.41 1 0 0 )41.2( 8 0 )

30.9( 6 0 )

20.6( 4 0 1

10.3( 2 0 )

P ressure

.:

:

100

'•

"

- :

-

90

18.5 37.0 55.6 74.1 92.6 111.1 129.6

D i s t a n c e , k m

F I G U R E 6-57 .—Variat ion of f l igh t - leve l windspeed and pressu re(ext rapolated to surface pressu re ) at an alt i tude of 3048 m (10 000

f t ) d u r i n g th e N O A A C-130 ai rcraf t pene t rat ion o f H u r r i c a n e A v a ,

J u n e 6, 1973.

wi nds pe e d . Th e circles indicate th e posi t ion of the cells

observed by the R A D S C A T i n s t r u m e n t. Th e win d vec-tor at each posi t ion can be obta ined d i rec t ly from th echa r t by proper in te rpola t ion .

Th e backscat ter coefficients were derived separatelyfo r each cell and t ime, corrected for a tmospheric a t -t e n u a t i o n a s o b t a i n e d f r o m t h e s i m u l t a n e o u sradiomete r measurements , and cata loged fo r eachpolarizat ion and incidence angle . Al l measurementswere referred to the five nomina l inc idence angles bycorrect ing the values of the backscat ter coefficients forsmal l deviat ions from th e nominal angles .

To es tabl ish th e de pe nde nc y of the backscat tercoefficients on windspeed or of the windspeed on the

backscat ter coefficients , two methods were used. In thefirs t method, a l l backscat ter values were t ransformed toupwind direct ion by us ing the measured effects of winddi rec t ion (by the Advanced Ap pl i ca t ion s F l ight Exper i -m e n t R A D S C A T P r og r a m ) as a convers ion fac tor .Th en , using the forma l pow er rela t ion obtained from anupda ted theory of backsca t t e r , which inc luded theeffects of win d direct io n, a regression analy s is was per-formed to minim ize the va r i ance be tween the predic tedradar wind veloci ty U r and the meteorological windveloci ty U m . The relation used in the ana lys i s was ex-pressed in both loga r i thm ic and pow er l aw form as

"

( m / s e c )

^knots) = V

(6-23)

The computed coefficients bQ,b { an d /30,/3, fo r pre-

dic t ing the windspeed f rom the backsca t t e r a re shownin t ab le 6 -VI for the log model and in table 6-VII for the

powe r la w model , re spec t ive ly . These tables show th esen s i t iv i ty of calcula t ions of the windspe ed to changesin radar cross sect ion as a funct io n of both po lariza t ion

and incidence angle , and indicate that the larges tchanges in backscat ter for a given change in windspeedoccur between incidence angles of 30° and 50°. The in-verse of the paramete rs w as also computed and showedthat bet ter agreement was obtained for the power lawbecause of more uni form weight ing of the l owerwindspeeds .

In the second method, th e predicted radar wind is ex-pressed as a c om b i na t i on of u p w i n d , d o w n w i n d , andcros swind ve loc i ty components and the aspect angle( the angle be tween th e wi n d d i r e c t ion and the a n t e nnadi rec t ion) . By an i t e ra t ive method us ing both poly -nomia l and powe r la w re l a t ions , an effective powe r la w

is obta ined fo r de t e r m i n i ng new coefficients , w h i c hare now func t ions of the aspect angle. The nonl inea rre lat ions used in the i tera t ion process indicated th at thedeviat ions could be im pro ved if the data w ere s t ra t i f iedfo r d i f fe rent wind-range in te rva l s . The da ta w erefur ther s tra t i f ied according to the source of the surfacet ru th , such as weather research ships ( type A) oraircraf t , and t rans ient ships ( types B, C, and D), andwere used fo r final error analys is .

To conf i rm th e consis tency of the results , th evar iance of the sur face - t ru th va lues and the radar valuesof windspeed were first sepa ra te ly comp uted . The sur-face- t ruth windspeed va r i ance was ob ta ined us ing a

wi thhe ld wea ther sh ip ana lys i s , in which the va luemeasured by the weather ship w as assumed to be thet rue windspeed . The variance of the radar windspeedva lues w as obtained by c om pa r i ng th e windspeedvalues obtained at the four different pola r i za t ions fo reach cel l . I t was then assumed that, if the results wereconsis tent , the tota l variance of the difference betweenthe meteorologica l wind and the rada r wind should bethe sum of the two variances . The results are shown intable 5-III in section 5. Residual variances are general ly

obta ined only when th e sample sizes are smal l . Thisf inding increases th e confidence that th e assumed

F I G U R E 6-58.—Composi te s treamline-isotach analys i s fo r Hur-

r i c ane Ava , J u n e 6,1973. Th e stream lines (s olid) show th e d i re c t i onof a i r f low . Th e isotachs (dashed lines) show windspeed in meters

p er second (k n o t s ) . —«.

3 3 2 S K Y L A B E R E P I N V E S T1 G A T IO N S S U M M A R Y



noLongitude, d e g W

DATA A N A L Y S I S TECHNIQUES 333



models and techniques used are val id and tha t th e radarvalues, w hich ha ve a constant var iance of 0 .98 m/sec(1.9 kno ts) squared, are general ly more rel iable than thevalues obtained f rom ship observations.

T h e b r i g h t n e s s t e m p e r a t u r e a n d b a c k s c a t t e ranomalies measured by the SI93 over a ground t r ack in

Texas on June 5,1973, were related to the 5-day API byMoore et al . (ref . 6-59) as previously descr ibed. The 5-day API is a convenient moisture parameter because itrequires only th e daily prec ip i ta t ion , wh ich is rou t ine lyrepor ted by the weath er s ta tions . However , it is k n o w nt h a t th e ac tua l soil mois tu re con ten t m a y b e considera-bly d i f f eren t f rom th e value predic ted by the 5-day A PI

because it neglects the effects of the soil type and therunof f routing on the surface.

To establ ish a more accurate ground- truth base ofsoil moisture for both SI93 and SI94 measurements ,Eagleman et a l . (ref. 6-60) determined th e soil moisturedirectly a long th e ground t r ack of the satellite. Soil sam-

ples , collec ted at 7 -km inte rval s near the t ime of theSkylab over f l igh t fo r each 2.5-cm layer down to a d ep t hof 15 cm, were weighed and dried in the l abora to ry , andth e soil moisture (i n percentage by weigh t ) fo r eachlocat ion and layer was de termined . To compare theS k y l a b m e a s u r e m e n t s w i t h t h e g r o u n d - t r u t h s oi lmoisture values, the sampled soil moisture values were

T A B L E 6- VI.— Linea r Regression Estimates of BackscatterCoefficients

a

[ l o g u .(m/sec)

Nadir

angle,

deg

50

4 ;

,;

17

:

Polarization b f

(b)

\\

HH\ H

l l \

\ \

i l l l

\ I I

H \

\ \

H H\ i i

HV

V V

HHV HH \

V V

HHV HHV

0.0290

.0301

.0311

.0322

.0260

.0277

.0317

.0303

.0342

.0345

.0238

.0276

.0827

.0706

.0905

.0887

-.1163

-.1148

-.1425

-.1383

Estimated

standard

error of bt

0.0027

.0025

.0025

.0026

.0023

.0023

.0023

.0023

.0030

.0031

.0021

.0022

.0100

.0098

.0116

.0112

.0179

.0177

.0167

.0158

*o

1.387

1.541

1.786

1.811

1.279

1.389

1.762

1.721

1.236

1.271

1.445

1.545

.731

.737

2.164

2.131

2.368

2.349

.274

.291

Standard

error of b

0.159

.154

.150

.149

.149

.144

.133

.137

.134

.136

.133

.128

.190

.198

.195

.195

.218

.223

.208

.206

N o. of

observations

124

121

1101 14

1 3 4

133126

12 7

147[4614 1

[4 1

14614 5M i ,

141

[3414

136136

aThe scat te r ing coeff ic ients were adjus ted to u p w i n d direc t ion and the n a d i r angks l is ted be fore

regression.

VV, ve rt ical t ransmit , ve rt ical rece ive ; HH, horizon tal t ransmit , horizon tal rece ive ; VH, ve rt ical

t r a n s m i t , horizontal receive; HV, horizonta l tra nsm it, vertical receive.




interpolated both in t ime and space by using thec l i m a t i c w a t e r - b a l a n c e t e c h n i q u e d e v e l o p e d b yThorn thw ai te and M ather ( r ef . 6 -63) . In th i s method ,the po ten t ia l evapo t r ans p i r a t ion r a te i s es timated f romthe mean daily tem pe ratu re and the value is adjusted toth e day of the yea r and to the lat i tude. The ac tual

evapotranspirat ion is then computed f rom the est i -mated potential evapotranspirat ion rate, th e prec ip i ta -t ion, and the available soil moisture, which depends onth e soil type at the given location. Con tour m aps of theresul tant soi l moisture, such as that shown in f igure6-59(a), were then produced.

Similar dis tr ibutions of S193 br ightness tem pera ture

TABLE 6- Vll.—Power L aw Regression Estimates

of Backscatter Coefficients

["knots,

Nadir Polarization /}

angle. (b)

deg

50

43

32

15

0

al k n o t -

* > V V vcr l i

V V

HHV HHV

V V

HHV HHV

V V

HHV HHV

V V

HHV H

HV

V V

HHV HHV

0.5144 m/sec.

i l l t ransmit \

82.87

102.5

137.2

140.9

61.64

84.40

136.1

134.0

36.41

42.55

75.90

75.75

11.82

12.16

279.8

206.4

373.2

529.3

4.250

3.571

'^rtiral rprei

B Numb er ofi

cases

0.4196

.3748

.3263

.3318

.3881

.4000

.3414

.340

.3594

.3847

.2881

.2878

.6284

.484

.8778

.7924

- 1.070

-1.182

-1.345

-1.533

i / * > - HH hnrm

124

121

110114

134

133

126

127

147[46

141

140

146144

136

141

134

140136

136

intal t r ansmi

rms difference

5.5

5.2

4.4

4.4

5. 2

4.94.14.2

3.8

3J3.73.7

4.7

5.2

4.95.0

4.74.74.7

4.2

VH, ver t i ca l t r an s mi t , hor i zont a l r eceive; HV , hor i zont a l t r ans mi t , ver t ic a l r eceive .

and backscatter were der ived and are shown for thesame test site in figures 6-59(b) and 6-59(c), respec-t ive ly . The large footpr int of the S194 radiometer obser-vations did not permit presentat ion of such a high-resolution dis tr ibu tion , and a com par ison betwee n theSI94 data and the ground- truth soil moisture was ob-

tained by weighted a veraging of the soil moisture con-tent wi th in the foo tp r in t .

The results of the analysis of five passes ind ica te tha tth e highest correlation w as obtained between th e 21-cm(S194) br igh tness tempera tu re and g round- t ru th so i lmo isture (fig . 6-60) because the 21-cm radio m eter ismore sensit ive to soil moisture than th e 2.2-cmR A D S C A T and is less sensitive to surface roughnessand atmospher ic var iat ions. Th e equ iva len t com par i sonbetween th e 2.2-cm br ightness temperature and soilmoisture is show n in figure 6-61 for the Texas test siteused by Moore (ref. 6-59). Th e correlation increases, inth is case, f rom —0.76 with a 5-day API to -0.91with

th e direc t soi l moisture content determination. A com-parison of soil moisture with th e backscatter measure-ments , however , shows a reduced correlation.

A compar ison of the different sensor sensitivities tosoil moisture is shown in figure 6-62 for the same sizeresolution cell. The poor response of the backscattermeasurements is believed to be due to the large inci-dence angle (30°), at w h i c h roughness effects dominateth e response. O ther significa nt results of Eagleman'sanalysis indicate that hor izontal polar izat ion radiome-try at 2.2 cm is less sensitive to soil mo isture tha n is ver-tical polar izat ion, that th e best correlation is obtainedwith the top 2.5-cm-layer soil moisture, and tha t th e

height of the vegetation cover m ay m o d i f y th e soilmoisture measurements .

Th e per fo rmance of microwave sensors of soilmoisture as a func t ion of incidence angle w as investi-gated by Stucky (ref. 6-21). Fo r th is purpose, th e J u n e11 pass over Texas, made using sensors that operated inth e intrack-contiguous mode , w as selected. The soilmois tu re parameter w as expressed as the API for 11and 6 days wi th a recession value (i.e., loss of moisturedue to evapotranspirat ion an d subsur face runof f ) of0.9. Th e daily precipitat ion w as l imited to 5 cm becauseit w as assumed that any excess value would p roducerunoff and would not contr ibute to soil moisture. Inter-

polat ion between stat ion API 's and the API 's at thefootpr int center w as obtained by a dis tance-dependentcircular weigh ting function that com bined at least threestation API's.




Texas

Soi l moisture, percent

| | O t o 5

[ j 5 to 10

10 to 15

15 to 20

20 to 25

(a

FIGU RE 6-59 .—Geographic d i s t r ib ut ion of var ious pa ra m e t e rs over

th e Texa s test si te , J u n e 5,1973 (S ky lab 2 pass 5). (a) Soil moisture

content , (b ) S193 radiometric t em pera t u re , ( c ) S193 scat ter ingcoeff ic ient .

A rela t iv ely high co rrela t io n of soi l mois ture with2.2-cm brightness temperature was obtained only forsmall incidence angles and for the 10-day API (fig.6-63) . The 6-day API neglected s ignif icant contr ibut ionto soi l mois ture of earl ier precipi ta t ion, and a t the largerangles, th e effect of sur face roughness and the at-mospher i c va r i a t ions became m or e s igni f i cant . C or re la -t ion coefficients between brightness tem per ature andback scat ter decreased l inear ly w ith increas ing inc idenceangle , s t a r t ing wi th a m a x i m u m of —0.95 at 2° na d i r

angle .McFarland (ref . 6-21) used th e concurrent S194

measurem ents for comp ar i sons wi th comp uted A PI ' s.

TexasS193 radiometer antenna

temperatures, K

Less than2 55

25 5 to 260

260 to 265

2 6 5 to 270

270 to 275

27 5 to 2 8 0

280 to 285

| J M ore than 285

Texas

S193 scatterometer return, dB

M ore than -8 .0

-8.0 to-8.5

-8.5 to-9.0

-9.0 to -9.5

-9.5 to -10.0

-10.0 to -10.5

Less than -10.5

(c )

3 3 6 S K Y L A B E R E P I N V E ST I G A TI O N S S U M M A R Y



-

-

- •

240

230

2 2 0

£ 27 0 r

2 5 0

2 4 0

230

2 2 0

210

Id)

0 5 10 15

Soil moisture, percent by weig ht(a )

0

(b )

5 10 15 20

Soil moisture, percent by weig ht

0 5 1 0 15Soil moisture, percent by weight

(c )

2

10 15 20

Soil moisture, percent b y we igh t

2 5 3 0 10 15 20 25

Soil moisture, percen t by weig ht

3 0 3 5

F I G U R E 6-60.—The relationship between S194 brightness temperature and soil moisture content for five separate data sets. The correlat ioncoefficient ri s s hown fo r each set. (a ) Texas, pass 5; r = -0.99. (b) Texas, pass 16; r = -0.96. (c ) Texas, pass 38; r = -0.98. (d ) K ans as ,pass 10; r 0.95. (e ) Kansas , pass 38; r = -0.97.

Excel lent agreement was obtained with the 11-day APIas shown in figure 6-64,but another pass showedanomalies that could be correlated with i r r igation andcul t ivat ion. Thus , a l though th e 11-day A PI represents a

good estimate of soil moisture, there are areas in whicha remote sensor such as the S194 would produce a moreaccurate dete rmi nati on of the true soil mois ture con-tent .




290r.

-

2 7 0

.-

I260

:10 15 20

Soil moisture, percent by w e i g h t

F I G U R E 6-61.—S193 antenna temperature as a f u n c t io n of soil

mo is tu r e c o n ten t f o r t he Texas site, pass 5, a t 29.4° pi tch and VVpo la r i z a t io n (r = -0.91).

29 0r

-

2 260

a.fO

£ 250

S193 2 . 2 - c m rad iometer , r = - 0 . 9 8 8

5194 21-cm rad iomete r , r = -0.996

S193 2 . 2 - c m scat terometer,

r = 0 . 7 5

•10 i=

10 20

Soil mois ture , percent b y we igh t

F I G U R E 6 - 6 2 . — A c o m p a r i s o n of t h e response of t h e t w o

r ad io me te r s an d the s c a t t e r o me te r to t he s o il mo i s tu r e c o n ten t wh enaveraged for the same size resolution cell.

-1.0 r

-0.8 -

,10-day A P I

20 30

Incidence angle e, deg

I

F I G U R E 6- 63 . —C o r r e l a t io n of S193 appa r en t b r ig h tn es s t em-

peratures w i t h t he 6 - an d 10 -day w e ig h ted AP I sets fo r f ive i n c i -

den c e an g le s .

7r 2 2 0 r

•

'

230h£

_ oT

I240

o>

t;250CO

0>c

^t2 6 0.0

§

" 2 7 0

-

11-day A P I

0 2 0 40 60 8 0 100

M easurement point

:

F I G U R E 6-64.—S194 L-b and br ightn ess temperatu re and f o o t p r i n t

av e r ag e of 11-day API for June 11, 1973. The 5-day API da ta are

sh ow n fo r c o mpar i s o n .




S U M M A R Y

The re sul ts of the S kylab E R E P p h o t o g r a p h i c e x p er i-m e n t de m ons t r a te t ha t s e ns i t om e t r ic a l l y c on t r o ll e d ,m u l t i b a nd photography cons t i tu tes a p o wer f u l tool fo rinvest igat ing Ear th resources prob lems . The m ul t iba nd

characteris t ics of the pho t og r a ph i c da ta w e r e crucial fo rboth v i sua l and m ach ine ana lys i s of the da ta . The threemost des i red improvements in the pho t og r a ph i c da t aare larger scales , bet ter resolut ion, and mo re freque ntcoverage. Th e l a rge r s ca l es would make machineanalys is of the data s impler because image densi tome-try of an object becomes easier as the image size of theobject increases . Improved resolut ion would ass is tvisual and m achin e in te rpre ta t ion and increase ana lys i s

accuracy . T h e desire fo r m or e f r e q ue n t and repet i t ivecoverage i s not endem ic to the p hotog raphic exper i -ment ; inves t iga tors us ing o the r sensors also expressedth i s need. However , th e demons t ra ted abi l i ty to ha nd l e

a tmospher i c and proces s ing d i f fe rences occur r ing be -tween coverage dates h as improved th e potent i a l va lueof mul t ida te ana lyses and has undoub t e d l y led to in-

creased requests for such cov erage. Image digi t izat ionand c om pu t e r a na l y s i s of photographic da ta offer

perhap s the mos t s igni f i cant and ad aptab le ana lys is ap-proach for complex , mul t ida te prob lems , and rea l i za -t ion of the potent ia l of this form of image analys is ison l y beginning.

The electr ical recording of mul t ichannel data fromthe S I92 Mul t i spec t ra l Scanner enab led use of a wide

range of s ignal -process ing techniques and led to severaldeve lopments in da ta manipula t ion by which the ad-

vantages inherent in mult ispectra l remote sensing canbe appl i ed . In some cases, s ingle bands outs ide th ephotograph ic region showed suf f i c i ent cont ra st and pro-v ided informat ion for a pa r t i cu la r use . Examples in -c lude the use of the 1.2- to 1.3-jtm b a nd fo r correla t ionto e l ec t ri ca l cond uc t iv i ty or s a l in i ty , the the rm a l bandto he lp d i f fe rent i a te commerc ia l - indus t r i a l - res ident i a lland uses from natural vegetated areas , and the 1.55- to1.15-fj.m band to sepa ra te w a te r fow l hab i t a t s f rom other

land features .The d ig i t a l forma t enab led machine enhancement of

deta i l by contras t -s t retching a part icu lar range of s ignalsto ma tch the d i sp l ay med ium. By color t rans la t ion and

by over l ay ing images f rom two or m ore bands , im-provements in d i s c r i m i na t i on of features in wa t e r ,

geological, and agr i cu l tura l scenes were demons t ra ted .

Th e tape recording of the several channels a lso per-mi t t ed the ra t io ing of a p a i r of channe l s tha t a ided inth e separat ion o f fer r ic , fe r rous , and non fe r ro us c l a ssesof materia ls . The ra t io of spec tra l band s in the red/g reenregion resul ted in bet ter correla t ion with suspendedsolids in rese rvoi rs than e i the r indiv idua l band . The

rat io o f inf ra red / red spec t ra l bands w as f o u n d usefu l incorrela t ing soi l mois ture differences in the presence ofpart ial vegetat ion cover.

Th e full poten t i a l of the m ul t i spec t ra l da ta s e t wasrealized wh en c om pute r ana lys i s of the ent i re spec t ra lrange was pe r formed. Subse t s of opt imum spec t ra lbands were chosen by various s ta t is t ica l decis ionalgori thms, and compute r recogni t ion of objects byus ing both supervi sed and unsupervi sed c l a s s i f i ca t iontechniques w as achieved wi th va ry ing degrees of suc-

cess. Modif ied c lus te r ing t echniques led to reducedmachine t ime, higher class if icat ion accuracies , and im-proved man/machine in te rac t ions .

Clas s i f i ca t ion accurac ies were improved by us ingdifferent preprocess ing rules . Atmospheric effects inth e da ta were removed to improve accuracies , and at-mospher i c e f fec t s on the choice of channe l s were ex -plored . Mix ture -proc es s ing t echniques were used to im-prove resu l t s whenever th e resolut ion element con-ta ined a mix ture of ob j ec t s such a s found nea r bound-aries between classes. Signature-extension schemes

were explored an d inform at ion about e l eva t ion , a spec t ,and s lope helped to improve recogni t ion accuracies ,part icular ly fo r scenes of mounta inous regions . The useof statistical factor analysis in ^-dimensional space,

whe r e W i s t h e n u m b e r of spectra l bands , w as explored

and foun d va luab le in the enhancemen t of rock outc ropand dense vegetat ion.

The SI 92 data a lso were used in s tudies of ur b a nmicroc l ima te and in ve r t ica l w ind prof i le analyses . Theva lue of mul t iband scanner da ta w as demons t ra tedespecia l ly for bands beyond those now ava i l ab le inLandsa t . These should be incorpora ted in fu ture spacesensors.

The S191 Infrared Spectrometer data were useful inob ta in ing informat ion about the spec t ra l t ransmis s ionof the a tmosphere and reflect ion characteris t ics of ter-

ra in classes. Rat ios of spectral emissivities in the shor t -and long-wave length bands are useful in d i f fe rent i a t ing

basal t ic rocks from daci te . The S191 data were used inth e s tudy of the ocean color spectrum. Resul ts agreedwel l wi t h measurements for wavelengths greater than




0. 5 A i m . M or e da t a on aerosol propert ies are needed toachieve s imilar resul ts fo r wa ve l e ng t h s less t han 0. 5

Aim.

T h e m a j o r ob j e c t i ve s a c h i e ve d b y t h e E R E Pmicrowave inves t iga tors can be s um m a r i ze d in threeareas: sensor perform ance eva lua t ion , bui ld ing of a da ta

base fo r m i c r owa ve sensor sys tem design,and es tabl ish-ment of potent i a l appl i ca t ion a reas .

Th e al t imeter precis ion w as va l ida ted , and m e t hodsfo r de t e r m i n i ng and cor rec t ing fo r poin t ing-angle andorbi ta l errors were developed. Ocean radar cross sec-t ions for a lt imete r opera t ion w ere de te rmined w i th h ighprecis ion, the electromagnet ic reflect ion mechanism forboth ocean and t e r ra in w as es tabl ished, and measure-ments of t e r ra in topography were shown to be feasible.

Th e sca t t e romete r obse rva t ions provided a large database of backscat ter coefficients as a function of surfacereflect ing and scat tering propert ies , incidence angle ,and po l a r i z a t i on , and es tabl ished th e sensit iv i ty of a

sca t te romete r to windsp eed for a large range of surface-t ru th windspeed values . S imilarly, a large data base ofbr ightnes s - t empera ture va r i a t ions over th e ocean andterra in was cata loged for different surface condi t ions ,incidence angles , and polarizat ions . Theoret ical re la-t ionship s between varia t io ns of the ph ysica l oceanparamete rs of sa l in i ty , surface wind, and sea-surfacet e m pe r a t u r e and the ocean br ightnes s t emp era ture weredeveloped an d verif ied with th e SI94 measurements .Potent ia l ap pl ic at ion for determin ing soi l m ois ture bylong-wave length rad iomete r obse rva t ions w as con-firmed.

Th e results of the microwave inves t iga t ions have

both short - a nd l ong- te rm impl i ca t ions . Th e exper iencega ined wi th the Sky lab a l t imete r was imm edia te ly ap-pl ied to the design and opera t ion of the Geodetic E a r t hOrb i t ing Satel l i te C a l t imeter , which is now in orbi t .F u r t h e r r e f i n e m e n t s a re p l a n n e d fo r the Seasata l t i m e t e r ( to be l a u n c h e d in 1978) . T h e Seasatspacecraft wil l also include an improved vers ion of ascatterometer t ha t can de te rmine both windspeed andwind d i rec t ion .

Th e results of the S kylab al t imeter terra in observa-t ions provide bas ic informat ion for improved sur facet opog r a phy de t e r m i na t ion by a l t i m e t r y if the a l t imete r

sampl ing capab i l i ty of the radar return is e x pa nde d .

This concept is being considered for the Space Shut t l e ,w h i c h w i l l o r b i t th e E a r t h , a n d f o r u n m a n n e dspacecraft that will or b i t th e M o o n and the planets .

The cata log of backscat ter coefficients and bright-ness t e m pe r a t u r e s will he lp rada r and radiomete r de -s igners to provide op t im um m icrow ave sys tem per -fo rmance for a variety of ap p l ica t io n s .

F in a l ly , th e ava i l ab i l i ty of higher spatia l resolut ionperformance of pass ive m icrow ave sensors at the longer

wave l eng ths wil l enable s ignif icant globa l synopt i cmeasurements of soi l mois ture con tent .

R E F E R E N C E S

6-1. Potter, A. E.; Grandfield, A. L.; and W illiams, C. K.: FlightPe r fo rm ance o f t h e S ky lab E ar t h Re s ources E x p e r i m e nt

Package . The S ky l a b Result s , Advances in the Ast ronaut ical

Sciences, vol. 31 , p t. 2 , W i l l i am C. Schneider and T h o m a s E .

Hanes , eds ., A merica n A st ronaut ical Socie ty (Tarzan a,

Calif . ) , 1975, pp. 605-633.

6-2. Pir ie , Douglas M. ; and SteUer , D avi d D . : Ca l i fo rn i a Coas ta l

Processes Study. NASA CR-144489 , 1975.

6-3. Barnes, James C :; S m al lw ood , M i ch ae l D.; and Cogan ,

James L. : S tudy to Develop Improved Spacecraf t Snow

S u r v e y M e t h o d s U s i n g S k y l a b / E R E P D a t a . N A S A

CR-144388, 1975.

6-4. S ze k i e ld a , Kar l - H e i nz : D yn am i cs o f Plank t on Pop u la t ions in

U p w e l l i ng Areas . NASA CR-144480, 1975.

6-5 . Piech , Ke nn eth R. ; Schot t , Joh n R. ; and Stewa rt , Ke nton

M.: S190 Inte rpre tat ion Techniques Dev elopm ent and Ap-

pl ica t ions to New Y ork State W ater Resources . N AS A

CR-144499, 1975.

6-6. Ba ldridg e, Pau l E.; Goesling, P. H.; et al. : Uti lizin g Sk yla b

Data in On-Going R esources M ana gem ent Program s in theState of Ohio. NASA CR-134938 , 1975.

6-7. Yarge r , Harold L . ; and M cCa uley, James R. : Sky lab Study of

W at e r Q ua l i ty . NA S A CR- 1 4 4 5 0 5 ,1 9 7 5 .

6-8. Gordon, H ayd e n H . ; and N i ch o l s , M aynard M . : S ky l a b M S S

Versus Photography fo r Estua rine W ater Color Class i f ica-

t ion . Wat e r Co lo r and Ci r cu la t i on S ou t h e rn Ch e s ap e ake

Bay , Par t II . NASA CR-141404, 1975.

6 -9 . W e lby , Ch ar le s W. ; and L am m i , J . O . : U t i l iza t i on o f E RE P

D at a i n Ge o log ica l E va lu a t i on , Re g i ona l P lann i ng , Forest

M a nage m e nt , and Wat e r M anage m e nt i n Nor t h Caro l i na .

NASA CR-144104, 1975.

6-10. Har dy , Ernest E . ; Skaley, J . E . ; e t al . : Enh ance men t andEv a lu a t io n of S ky lab Ph o t ograp h y fo r Pot e n t ia l L an d U se

Inventories . Part I and Par t II . NASA CR-144473, 1975.




6-11 . Colw ell , Robert N .; B e ns on , And re s S. ; e t al.: A gr i cu l t u r a l

In t e rp re t a t i on T e ch n i q ue D e ve lop m e nt . NAS A CR- 1 4 4 4 8 6 ,

1975.

6-12. Si lva, Leroy F . : A Study of the Ut i l i zat ion of ER EP D ata

From t h e Wabas h R i v e r Basin. NASA CR-147412, 1976 .

6 - 1 3 . Gum e rm an , George J . ; Hans on, Joh n A . ; e t al .: The Hy-drology of Pre h i s t o r i c F arm i ng S ys t e m s in a C e n t r a l A r i z o n a

Ecotone . NASA CR-144492, 1975.

6-14. Plogg, F.; and Garr ett , C.: Exp la in in g Var iabi l i ty in

Preh is tor ic Sou thwe ste rn Wa ter Co nt rol Systems. Paper p re -

sented at the 35th A n n u a l M eet ing of the Socie ty for A me ri -

c an Arch e o logy (M e x i co C i t y , M e x i co) , 1 9 70 .

6-15 . Langley, Phi l ip G.; and Van Roessel, Jan: The Usefulness of

S k y l a b / E R E P S-190 an d S-192 Imagery in M ul t i s t age Forest

Surveys . NA S A CR- 1 4 7 4 39 , 1 9 7 6.

6-16 . Mau l, George A. ; Gord on , H ow ard R . ; e t a l . : An E x p e r i -

men t to Evalu ate Sk ylab Ear th Resources Sensors for Detec-

t ion of the Gulf S t ream. NASA CR-147454, 1976 .

6-17. Gi lmer , Dav id S . ; and W ork , Edgar A. , Jr . : Ut i l i zat ion of

Skylab (E R E P) S ys te m fo r Ap p ra i s i ng Ch ange s i n Co n t i -

ne n t a l M i gra t o ry B i rd H ab i t a t . NA S A CR- 1 4 7 5 4 2 , 1 9 7 5 .

6-18 . Vinc ent , R. ; W agner , H. ; Pi l lars , W . ; and Bennet t , C. :

Assessments of M a p p i n g E x p os e d F e r rous and F e r r i c Iron

Com p ound s Us i ng S ky l a b E RE P D at a . NAS A CR- 1 4 4 5 0 4 ,1976.

6-19 . Vincen t , R. K. ; and Pi l lars , W . W . : Sky lab S-192 Rat io Codes

of S oil , M i ne ra l , an d Rock S p e c t r a fo r Ra t io Image Se lect ion

and In t e rp re t a t i on . P rocee d i ngs o f th e N i n t h In t e rn a t i ona l

S ym p os i um on Re m ot e S e ns ing of E nv i ronm e nt , E nv i ro n -

mental Research Ins t i tute of M i c h . ( A n n A r b o r , M i c h . ) ,

1974, pp . 875-896.

6-20. Cu rran , Robert J. ; S alom ons on , V i nce n t V.; and S h e n k ,

Wi l l i a m : T h e Ap p l i c a t i on o f Satel l i te D at a i n th e D e t e rm i na -

t ion of Oce an T e m p e ra t u re s an d Cloud Characte r i s t i cs an dStat is t ics . N AS A CR-147539 , 1976.

6-21. Pi t t s , David E .; S as ak i, Y o s h i kazu ; an d Lee, Jean T., com-

pilers: Severe S t orm E nvi ronm e nt s : A S ky l a b E R E P F i n a l

Re p or t . N AS A T M X- 5 8 1 8 4, 1 9 76 .

6-22. Phillips, T. L. , ed . : LARSYS Vers ion 3. 1 User's M anu al . V o l.

2. L abora t o ry fo r A p p l i ca t i ons of Re m ot e S e ns i ng , Purd ue

Uni v . (We s t L afaye t t e , Ind . ) , 1 9 7 3.

6-23. Swa in, P. H.: Patte rn Rec ognition : A Basis for R e m o t e Sens-

in g Data Analys i s . NASA CR-130757 , 1973.

6-24. Goetz, A. F. H. ; A b r a m s , M. J . ; e t al . : Compari sons ofSkylab and Lan dsat Images for Geologic Ma pp ing in No rth -

e rn Arizona. NASA CR-147503, 1976 .

6-25. Sat t inger , I . J . ; Sadow ski , F . G. ; and Ro lle r , N. E . G.:

An a ly s i s of Re c re a t i ona l L and Us i ng Skylab D a t a . N A S A

CR-144471, 1976.

6 - 2 6 . Na le p ka , R. F . ; M o r g a n s t e r n , J.; et al . : S -192 A naly s i s : Con-

v en t io n a l and Special Data Process ing Techniques . NA SA

CR-144506, 1975.

6-27. Simonet t , David S .: A p p l i c a t i o n of S k y l a b E R E P D a t a fo r

L a n d U s e M a n a g e m e n t . N A S A C R - 1 4 7 45 7 , 1 97 6.

6-28 . Eberle in, R. ; Va nd erb urg , G. L . ; Rosenfe ld , A. ; and David ,

L . S. : E d ge and L i ne D e t e c t i on in E RT S Im age ry : A Com -

pa r a t iv e S t ud y . NA S A CR- 1 38 9 6 3 , 1 97 4.

6-29. Anderson, Theodore W.: An Introduction to Mult ivar iate

Stat is t ical A nalys i s . John W i l e y & Sons, Inc . , 1958 .

6-30. Rao , C. R. : Line ar Stat i s ti cal Inte r fe ren ce and I t s Ap plica-

t ions . Joh n W i ley & Sons , Inc . , 1965.

6-31 . Swain, P. H.; Robertson, T. V. ; and W a c k e r , A. G.: C o m -

pari son of the Divergence and B-Dis tance in Feature Se lec-

t ion . L A RS In form at i on Not e 0 2 08 7 1 , Purd ue U ni v . (West

Lafayet te , Ind.), 1971.

6 - 32 . H of fe r , Roge r M . : Com p ut e r - A i d e d An a lys i s o f S ky lab

Mu l t i s pec t r a l S canne r D a t a i n M ount a i nous T e r ra i n fo r

Land U se , Fores t ry , Wa ter Resource , an d Geologic Applica-

t ions . NASA CR-147473, 1975.

6-33. Thomson, F. J.: M a c h i n e Processing of S-192 an d Support ing

A i r c r a f t Data: S tud ies of At m os p h e r i c E f f e c t s , Ag r ic u l tu r a l

Clas s i f i c a t i ons , and L a n d R e s o u rc e M a p p i n g . N A S A

CR-144503, 1975.

6-34. W iegand , Cra ig L . ; Richardso n, Ar thu r J . ; e t al . : Soil Salinity

Detect ion. NASA CR-144403, 1975.

6 - 35 . H annah , Joh n W . ; T h om as , Gar land L . ; E s p arza , F e rnand o ;and M i l l a r d , J. J. : Plann i ng Ap p l i c a t i ons in E as t Ce n t ra l

F lorida. NASA CR-145415, 1975.

6 - 36 . M cM ur t ry , George J . ; and Petersen, Gary W . : In t e rd is c i p l i -

n a r y Ap p l i c a t i ons and In t e rp re t a t ions o f E R E P D at a W i t h i n

t h e S us q ue h anna Ri ve r B as i n . NAS A C R- 1 4 7 54 1 , 1 97 6.

6-37. Selzer, Robert H.: The Use of Computers to Improve

Bio med ic a l I m a g e Qua l i t y . Proceed ings of Fall Joint Com-

p u t e r Confe re nce , vo l . 33, pt . 1 , Dec. 1968, pp . 817-834.

6-38 . Horwi tz , Harold M .; Nale p ka , Ri ch ard F. ; H yd e , Peter D .;and Morganste rn, James P. : Est imat ing the Proport ions of

Ob je c t s W i t h i n a S i ng l e R e s o l u t i o n E l e m e n t o f a

Mu l t i s pec t r a l S canne r . Proceedings of the Seventh Inte rna-

t iona l S ym p os i um on R e m ot e S e nsi ng of E n v i ron m e n t , E n-

vi ronmental Research Ins t i tute o f M i ch . (Ann Arbor ,

Mic h . ) , 1971, pp. 1307-1320.




6-39 . Poulton, Charles E . ; and Welch , Rob in I . : Plan for the

U n i f o r m M ap p i ng of E ar t h Re s ource s and E nv i ron m e nt a l

Com p le x e s From Skylab Imagery. NASA CR-144484, 1975.

6-40. Houston, R. S . ; M a r r s , R . W . ; and B o r g m a n , L. E . :

Mul t i d i s c i p l i na r y Study of Wy om ing Test S ites . NA SA

CR-147719, 1975.

6-41 . Haefne r , Harold : Snow Survey an d Vegetat ion Growth in

th e S w is s A lp s . NAS A CR- 1 4 7 39 5 , 1 9 7 6 .

6-42. Goldman, Gary C.; and H orva t h , Robe r t : O il Pol lu t i on

D e t e c t ion and M oni t o r i ng F rom S p ace U s i ng S ky lab . NA S A

CR-144502,1975.

6-43. Trumbull, James V. A.: The Uti l i ty of Skylab Photoin-

te rpre ted Ea rth Resources D ata in Stud ies of M arine

Geology and Coastal Processes in Puerto Rico and the Virgin

Is lands . NASA CR-147437 , 1975.

6-44. Polcyn, Fabian C. ; and Lyzen ga, Da vid R. : Sky lab Rem ote

B a t h y m e t r y E x p e r i m e n t . NAS A C R- 1 44 48 2 , 1 9 76 .

6-45. Pease, Robe r t W . : M a p p i n g T e r re s tr i a l Ra d i a t i on E m i s s i on

W i t h a Scanning Radiometer . Proceed ings of the Seventh In-

t e rna t i ona l S ym p os i um on Re m ot e S e nsi ng of E nv i ronm e nt ,

E nv i ronm e nt a l Re s e arch Ins t i t u te o f M i ch . (A nn A rbor ,

M ich . ) , 1971, pp . 501-510.

6-46. Villevieille, A.; and W e i ll e r , A. B. : The Possibili ty ofE valua t i ng V e r t i c a l W ind Prof i les From Sate l l i te Data.

N A S A CR-147475, 1975.

6-47 . Al drich , Robert C .; D ana , Robe r t W .; e t al . : Evaluat ion ofSkylab (E RE P) D a t a fo r Forest and Range lan d S urve ys .

NA SA CR-147440, 1975.

6-48. Polcyn, Fabia n C .; Rebel , Diana L.; and Colw e l l , Joh n E.:

An a ly s i s of Hydrolo gical Featu res of Port ions of the LakeOnt a r i o B as i n Us i ng S ky lab and Aircra f t D at a . NAS A

CR-147456, 1976.

6-49. Colwell, J. E.: Bid i rec t ional Spect ral Ref lec tance of Grass

Canop i e s fo r D e t e rm i na t i on o f Above Ground S t and i ng

B i om as s. Ph . D . D i s s e r ta t i on , Un i v . o f M i ch . (A nn Arbor ,

Mich.), 1973.

6-50. Savastano, K J.: Applicat ion of Remote Sensing for FisheryResources Assessment a nd M oni t o r i ng . NAS A CR- 1 4 7 5 0 7 ,

1975.

6-51 . An ding , Dav id C.; and W a l k er , John P.: Use of S ky lab

E R E P Data in a S e a - S ur f ace T e m p e ra t u re E x p e r i m e nt .

NASA CR-144479 , 1975.

6-52. Ma li la , W i l l i am A.; and N a l e p k a , R i c h a r d F. : A t m os p h e r i c

Effects i n E RTS - 1 D a t a , and A d vance d In fo rm at i on E x t rac -

tion Techniques . Proceed ings of the S y m p o s i u m on Signifi-

c an t Result s Obtained From th e Earth Resources Tech-

nology Sate l l i te -1 , Godda rd Space Fligh t Cen ter (New C ar-

rol l ton, Md.) , Mar. 5 -9 , 1973, vol . I, sec. B , pp . 1097-1104.

6-53. Tingey, Dav id L. ; and Pot te r , John: Qu an t i tat i ve Determ ina-t ion o f S t r a t os p h e r i c Ae ros o l C h ara c t e r i s t i c s . NA S ACR-147444, 1975.

6 -5 4. And i ng , D . C . ; Kau t h , R . ; and T urne r , R . E . : A t m o s p h e r i c

Effects on Infra red M u l t i s p e c t r a l S e ns ing of Sea-Surface

T e m p e ra t u re F rom S p ace . NAS A CR- 1 8 5 8 , 1 9 7 1 .

6-55. McGoogan, J. T.; Leitao, C. D.; and Wells, W. T.: S u m m a r y

of S ky lab S- 19 3 A l t i m e t e r A l t i t ud e Re s u l t s . NAS A T M

X-69355, 1975.

6 -5 6 . M ourad , A . G . ; Gop a lap i l l a i , S . ; Ku h ne r , M . ; and F ubara , D

M . : T h e Ap p l i c a t i on o f S ky l a b Al t i m e t ry t o M ar i ne Ge oi d

D e t e rm i na t i on . N AS A CR- 1 4 4 372 , 1 9 7 5.

6-57 . Bro wn , G. S . : Red uced Back scat te r ing Cross Section (o-°)

D a t a F rom t h e S ky l a b S - 1 9 3 Rad ar A l t i m e t e r . NAS A

CR-141401, 1975.

6 -5 8 . S h ap i ro , A l lan ; T h orm od s gard , June M . ; and Okad a , J . M . :

Sk y lab A l t i m e t e r O b s e r v a ti o n s O v e r T e r r a i n . N A S ACR-144498, 1975.

6-59 . Moore , Richard K. ; Ul aby , Faw wa z T. ; e t al . : Design Data

C o l l ec t io n W i t h S k y l a b M i c r o w a v e R a d i o m e t e r- S c a t -terometer S-193. Vols. I and II. NAS A CR- 1 4 4 5 37 an dNASA CR-144538 , 1975.

6-60. Eagleman, J. R.; L i n , W .; et al.: Detection of Soi l Mois ture

and Snow Ch aracte r i s t i c From Sk ylab. NA SA CR-144485,

1975.

6-61 . Holl inger , James P . ; and Lern er , Robert M. : An alys i s of

M i c r o w a v e R a d i o m e t r i c M e a s u r e m e n t s F r o m S k y l a b .

NASA CR-147442, 1975.

6-62. Cardone , Vinc ent J. ; Y o u n g , J a m e s D.; e t al.: The M e a s u r e -

me nt of the W inds Near the Ocean Surface W i th a

Radiomete j -Scat te rometer on Skylab. NAS A CR- 1 4 7 4 8 7 ,

1976.

6 -6 3. T h orn t h w ai t e , C . W . ; and M a t h e r , C . W . : Ins t ruc t i ons and

Tables fo r C o m p u t i n g P o t e n t i a l E v a p o t r a n s p i r a t i o n an d

W ater B alance . Publicat ions in C limatology, vol . 10 , no. 3 ,

1957, pp. 185-311.




A P P E N D I X A

E R E P Sensor Systems'

R O Y L . E A S O Nb

PRELIMINARY SENSOR SELECTION

The rationale for selecting the Earth Resources Ex-

p e r i m e n t Package (EREP) sensors was based on the

desire to explore various portions of the electromag-

netic spectrum; on the need for correlating data among

the various sensors; on the status of sensor develop-

ment; and on the adaptability of the sensors, as a

package, to the mission requirements. The sensor selec-

t i on , as first considered in 1969, resulted in the proposal

of four sensors.

For investigations in the visible portions of the

spectrum, the prime candidate was a camera system. A

m u l t i b a n d , high-resolution camera system was pro-

posed to provide data correlation with other remote-

sensor systems. The potential of the multiband camera

system was demonstrated during the Apollo 9 mission.

The spectral regions and film/filter-combination pro-

posals were based on experience gained during the

NASA Earth Resources Aircraf t Program, the Apollo

Program, and other multispectral photographic studies.The second sensor proposed was a wide-range imager

that would extend observations from the visible

through th e near-infrared into th e fa r- infrared portion

of the spectrum (0.5 to 2.4 /^m and 10.5 to 12.5 pm).

The shorter wavelengths were proposed to overlap the

m u l t i b a n d camera system. Other bands were proposed

to extend into the near infrared with the longer

wavelengths extending into the thermal in f ra red . The

longer wavelengths were to permit monitoring of night-

time surface emissions.

An infrared spectrometer was proposed to extend

measurements from 3.2 to beyond 14 pm. This

aThe pr i m a ry source of informat ion for this appendix was theSkylab EREP Inves t igator ' s Data Book.

' 'NASA Ly n do n B. Johnson Space Cen t e r .

wav elen g th range would provide correlation w i t h th e

wid e - r an g e imager at 10.5 to 12.5 /urn .

A microwave system that was a combination radar

scatterometer and passive microwave radiometer

o p era t in g a t approximately 10 GHz (3 cm) was pro-

posed. The advantages of this system were that it could

operate day o r night and that i t was not generally

affected by clouds and weather. Th e objectives of thissystem primarily concerned measurements of the

w i n d s over th e oceans, th e capabilityfo r snow mapping,

and measurement of rainfall. Portions of this type ofsystem had been used in the NASA aircraft program

and in t he Nimbus satellite program.

Later in the Skylab Program, three additional sensors

were proposed for the EREP system.

1. The L-band 1.4-GHz passive radiometer fo rmeasurement of soil moisture and oceanographic data

2. A radar altimeter applicable to both geodesy andoceanography (This system was to be capable of

measuring the distance from the spacecraft to the sur-

face of the oceans within an accuracy of 1 to 2 m.)3 . An Earth terrain camera system to provide higher

resolution data to serve as a truth source for the other

sensors and to assist those investigators interested in

m a p m a k i n g (This camera system was similar to the

high-resolution camera flown on the Apollo 14 mis-sion.)

THE EREP SYSTEM

T h e fol lowing f ive systems were selected fo r EREP.

(See fig. A-l.)

1. Th e Multispectral Photographic Facility (S190)

consisting of the Multispectral Photographic Cameras(S190A) and the Earth Terrain Camera (S190B)

2. The Infrared Spectrometer (S191)

3. The Multispectral Scanner (S192)

343





4. The Mic rowave Rad iometer /Sca t te rometer andA l t i m e t e r (S193)

5. The L -Band Rad iometer (SI94)

Figure A -2 shows th e wavelength coverage of theE a r t h - v i e w i n g E R E P S k y l a b s en s o r s . T h e E R E Pground coverage is shown in figure A-3.

Photograph ic Systems

Cameras provided th e p r i m a r y source of in fo rmat ionfo r mos t of the Skyla b investigators . The carefully

designed cameras and f i lms used for the E R E P w er en o t f u n d a m e n t a l l y d i f f e r e n t f r o m c o n v e n t i o n a lcameras and fi lms.

Images are formed on f i lms by dif fere nt wavelengthsor colors of light. Each film has a dif ferent sensit iv i ty toth e var ious waveleng ths of light. Figure A -4 shows th ewavelength sensit ivi ty of one of the Skylab f i lms (East-m an Kodak (EK) 3414). This film is similar to the com-

mercia lly availa ble Plus-X film; how ever, it is capab leof achieving higher resolution and is coated on a th in-ner base. Th e thin base permits a large volum e of filmto be packed into a small space.

The Skylab cameras used th e wavelength sensit ivi tyof the films to pho tograph th e Earth in well-defined col-

(••i Black-and-white film - 4bands

S190A limt Color-infrared f i l m - 1band

'mtmnH Color f i lm - 1 band

S190B §*MMM Color, color-infrared, or black-and-white film -1 band

S 1 9 2 |||||HHWM M

SI 93

S194

1 if

2 .4

:!::::;::-:

^. 2 b a n d s2 detectors

( 13 b a n d sj 13 detectors

1

H ; , - V i s i b l e spectrum

•x:m\ i

.6 .8 1

i i i i i i 1 1 1 1 1 i n

4 6 8 10 16

, N ,

~ 2 . 2 cm 21cmW a v e l e n g t h , Jim

F I G U R E A - 2 . — W a v e l e n g th s e n s i t iv i t y o f E a r th - v i e w i n g Skylab

sensors.

F I G U R E A-3.—The g r o u n d a r ea c o v e r ag e p r o v ided b y EREP sen-

sors (S-73-005-S).

or, or wavelength, regions by placing a filter over th ecamera lens. Th e effect of p lac ing a filter that t ransmitsonly red light over EK-3414 film is shown in figure A-5.

Use of the filter results in the film recording informa-tion in the red wavelength region only . Color f i lms donot need such filtration to record an image in spectralbands. A n ordinary color f i lm has three light-sensitivelayers, each of which is sensitive to a different group ofwavelengths. One f i lm layer records only blue light, asecond layer only green li gh t, and a thir d layer only redlight (fig. A-6). Th e information recorded on each ofthese film layers can be separated by means of severalanalysis techniques that are described in section 6 ofthis report.

Whereas standard color film has the normal b lue- ,green-, and red-sensitive layers (fig. A-7(a)), color-in-frared film does not have a blue-sensitive layer but in-stead has a layer sensitive to inf rared wavelengths.Because th e h u m a n eye is not sensitive to inf raredwavelengths, th e information on this film layer is made

EREP SENSOR SYSTEMS 345



h E R E P r a n g e -II Blue—H-—G reen—-\-—R ed—-|

j i i i i i i i2

250 300 350 400 450 500 550W a v e le n g t h , nm

600 650 700 750

F IGUR E A-4.— Wavelength sensi t iv i ty c urve fo r EK-3414 Him . FIG U R E A-6.—Cross sec t ion of a typical color emuls ion layer .

visible after development by having the infrared layerappear red. The red-sensitive layer is made to appeargreen, and the green-sensitive layer appears blue. Thisrather complicated situation in which red is not red andgreen is not green is depicted schematically in figureA-7(c) . The apparent confusion is more than justified,

however, by the amount of information obtained bymaking infrared wavelengths visible in a photograph.Color-infrared film is particu larly valuable in vegetationstudies. Figure A-7(b) contains a color-film image ofth e same scene shown in figure A-7(d) .

The photographic image is determined not only bythe film used but also by the camera. Three cameracharacteristics are most important: focal length, aper-ture, an d shutter speed. At a fixed distance, th e focallength of a camera determines th e size of an object rela-tive to the size of a photograph on which it appears.Thus, a telephoto lens with long focal length will make adistant object appear larger on a photograph than itwould appear if a short-focal-length lens were used. Along-focal-length lens will also provide better reproduc-tion or resolution than a short-focal-length lens of equalquali ty . The detail reproduction in a photograph can bel imited not only by lens distortions but also by film

grain. A view of exposed film under high magnificat ionw i l l reveal a nonuni form pebbly , or grainy, appearancecalled graininess. A long-focallength lens w i l l map asmaller object onto the l imit ing graininess to achievebetter resolution because of the small blur circle. Thefocal length cannot be increased arbitrarily. It is more

difficult an d expensive to make a high-q uali ty lens oflonger focal length. A long-focal-length lens also coversless area. The field of view (FOV) is decreased with along-focal-length lens, and a small FOV can be a disad-vantage in Earth resources studies.

Th e aperture and shutter parameters of a cameraaffect the amount of energy reaching the film duringth e exposure. Th e camera aperture (f-stop) representsthe ratio of the focal length to the diameter of the lensaperture. The amount of energy reaching the film isproportional to the square of the ratio of aperturediameter to focal length.

Multispectral Photographic Cameras (S190A).—Sixhigh-precision cameras with matched optical systemswere mounted an d boresighted to form th e camera as -sembly shown in figure A-8. Each camera had an f/2.8lens with an aperture variable to f/16 in 0.5-stop incre-ments and a focal length of 15.2 cm. At a nominal

s

I

I!• r 1

to1/1

1-1

R ed filter transmittance

( W ra t te n 25 filter).

Resulting sensitivity ( f i lm andfilterl--'

I I I I I I

2 50 300 350 400 450 500 550 600 650 700 750W a v e le n g t h , nm

F IGUR E A -5 .— W a v e l en g th sen s i t i v i ty c urve fo r EK-3414 filmshowing f i l tering to t r ans mi t only red l ight .

F I G U R E A-7.—Color as opposed to color- infrared spectral layer ,

(a ) Sensi t iv i ty c urve fo r color f i lm, (b ) Color photograph oft h e Y u m a , A r i z o n a , area taken o n J a n u a r y 2 6 , 1974

(SL4-92-356) . ( c ) Sens i t iv i ty cu rv e fo r color - inf rared f i l m .(d) Color- infrared photograph of the Y u m a , Arizona, area taken onJ a n u a r y 14, 1974 (SL4-93-057). —*-

346 SK YLAB EREP I N V E S T I G A T I O N S S U M M A R Y



100

E R E P S E N S O R S Y S TE M S 347



F I G U R E A - 8 . — M u l t i s p e c t r a l P h o t o g r a p h i c Cameras (S190A). (a) Magazines (S-72-4441S). (b) Lenses and f i l ters (S-72-44416).

spacecraf t al t i tude of 435 km, the 21.2° FO V providedground coverage of a square area appro xim ately 163 kmon each side (1:2 900 000 scale, approximately).

The f i lm wid th was 70 mm , the shu t ter speeds were2.5, 5, and 10 millisecond s, and the six shutter mecha-nisms were synchronize d to wi thin 0.4 mil l isecond.Programe d cam era rota t ion, var iable f rom 10 to 30mrad/sec , c ompensated for the forw ard motion of thespacecraft , and pho tographs cou ld be taken singly or ina u t o m a t i c series in 2- to 20-second interv als. To pro vid efo r stereoscopic v iewing , 60-percent overlaps were ob-tained using 10-second intervals .

Figure A -9 shows si x sample images acquired by the

SI90A cameras and inc ludes information on film typesand spectral ranges. Th e S190A data were usual ly fur-nished to the Pr incipal Investigators in the form of con-tact positive and negative transparencies (70 mm ) andenlarged transparencies (280 mm).

Earth Terrain Camera (S190B).—The Earth ter rainsingle-lens camera assembly (fig. A-1 0(a)) had an f/4lens and a focal length of 45.7 cm with a focal-planeshutter. Programed camera rotation, variable from 0 to25 mrad/sec , compensated for the forward motion ofth e spacecraft. The 14.24° FO V provided groundcoverage of a square area app rox ima tely 109 km on eachside (1:950 000 scale, approx imate ly ) .

The film w i d t h w as 12.7 cm, and the shutter speedswere 1/100, 1/140, an d 1/200 second. Sequence photo-graphy intervals were possible f rom 0 to 25 f ram es/m in.

To provid e for s tereoscopic view ing, 60-percent over -laps were obtained using a rate of 9 .5 f rames/min.Figure A-10(b) is an image of an area taken wi th th eEar th Terrain Camera. Data were usual ly fu rn i shed toth e Principal Investigators in the form of posit ive andnegat ive contact t ransparencies (140 mm) and enlarged

transparencies (280 mm). Unless otherwise stated, "col-or film" should be assumed in S190B discussionsthroughout this repor t . The S190B film types used on-board the sp acecraf t were EK-3414 black-an d-w hitehigh-def ini t ion aer ial (0.5 to 0.7 /x m) , special order SO -242 high-resolution aerial color (0.4 to 0.7 /u rn) , SO-131

high-resolution color-infrared aerial (0.5 to 0.88 A < , m ) ,

and EK-3443 color-infrared (0.5 to 0.88

Station Wavelength, Film

1

:3

4

56

*""

0.7 to 0.8

0.8 to 0.9

0.5 to 0.88

0.4 to 0.7

0.6 to 0.70.5 to 0.6

Color

B l a ck -a nd -w h i t e

( B & W ) i n f r a r ed

B & W inf rared

Col or i n f r a r ed

Color

B & W vis ib leB & W v i s i b l e

Type

EK - 2424

EK-2424

EK-2443

Special o r de r

(SO) 356

SO-022SO-022

348 S K Y L A B EREP I N V E S T I G A T I O N S S U M M A R Y



Stat ion 1

Stat ion 3

i Stat ion 5

\

Station 2

Stat ion 4

Stat ion 6

FIGURE A-9.—S190A sample data taken over L as Vegas, Nevada; Lake Mead; th e Colorado River; and the Hoover Dam. Data on fi lm

parameters fo r each station ar e conta ined in the table on the facing page.




M agazine

assembly

(a )

-Lens cone

Camera control

box

.„- Forward motion

compensationmechanism

F I G U R E A-10.—Earth Terrain Camera (S190B). (a) C a m e r a as-

s emb ly , (b ) Sample da ta taken o v e r n o r t h w e s t e r n F l o r i d a(SL3-88-141).

S pe c t r o r a d i om e t r i c Sensors

Remote sensing depends on receiving energy f roman object or a scene, viewing or record ing it, and ana lyz -in g the received energy to deduce s o me of the charac-teristics of the scene. In recording the energy of an

Ear th scene with a space sensor, th e many var iablesconsidered can general ly be divided into tw o classes:those var ia t ions tha t affect or in f luence some charac -teristics of the scene, such as t em p e r a t u r e an d mois tu re ,and those var iat ions that , al though they inf luence th eradia t ion received at the sensor, do not represent scenec h a r a c t e r i s t i c s . E x a m p l e s a re the i n t e r v e n i n g a t -mosphere and con tam ina t ion a round the r ecord ing in -s t r u m e n t . T h e m o s t i n f l u e n t i a l a g e n t w i t h i n th ewaveleng ths prev iously discussed is the atmosph ere.The al terat ions of radiat ion passing through the at-mosp here ha ve serious ram if icat ions for remote sens-ing. The S191 Infra red Spectrom eter was designed to in-

vestigate correc t ion fac tors that might be appl ied.A l t hough called an infrared spec t rometer , th e sensoroperated in both th e r ef lec t ive (0.4 to 2.5 / L t m ) an demissive (6.6 to 16 /iin) waveleng th in terva l s .

The basic pr in ciple concerned view ing a s inglehomogeneous scene long enough to record th e r ad iancevalues over th e entire wavelength range an d thereby ob-taining a plot of energy level as a function ofwavelength for the target scene. If the energy levelsdepar t ing f rom ground level are known (ei ther f romdirect measurements or by inference) and if they arecompared to the levels received at the sensor, th e m a j o rd i f f erences c a n b e a t t r i b u t e d to the i n t e r v e n i n g

medium. Even if there are no differences, how ever , onecannot assume th e medium has no effect. Fo r ex a m p l e ,at some waveleng ths , the med ium m ay comple te ly ab -sorb th e emissions of the ground scene an d replace th eabsorbed radiat ion with i ts own emissions. Th e exper i-menter relies on the spectral details of the compar isonto unravel th e confounding effec ts of the atmosphere.

Infrared Spectrometer (S191).—The S191 InfraredSpectrometer w as unl ike th e other visible an d inf raredrecording sensors (cameras and multispectral scanner)and also unl ike many other infrared systems in that noimage was acquired or der ived.

Th e S191 sensor ( f ig . A- l l (a ) ) w as composed of af il ter -wheel spectrometer that spectral ly scanned th eradia t ion enter ing it s aper tu re and a trackin g telescopealined along the spectrometer line of sight that enabledth e c rewman to acquire and t rack th e test site and take




-

io -3h

I I

H e l i c o p t e r

Carbon

d i o x i d e

• W a t e r v a p o r

ill)

9 11

W a v e l e n g t h ,

13

F I G U R E A-ll.—Infrared Spectrometer (S191). (a) I n s t r u m e n t ,

(b ) Sample data.

1 6 - m m ph otog raph s of the s cene . Inco min g radia t ion ,recorded at 1 spe ctra l scan/sec fro m a Cassegrainian col -l ec t ing telescope, w as sp l i t in to shor t -w ave length (0 .4 to2. 5 nm) and long-wav e length (6 .6 to 16.0ju.rn) b a n d s b ya dich roic beam spl i t t e r. The de tec tor a l t e rna te ly s ensedr ad ia t io n from t he ex te rna l ta rge t and f rom the in te rn a l

reference sources.Vis ib le and nea r - in f ra red energy was de tec ted by a

sil icon and lead su lf ide s a ndwi c h de t e c t o r ; t he r m a lenergy was detected by a m e r c u r y - c a d m i u m - t e l l u r i u mdetector that w as cooled to 90 K by a m i n i a t u r i z e dc l o s e d - c y c l e e n g i n e . I n - f l i g h t c a l i b r a t i o n s p e c t r arecorded before and after each da ta -ga the r ing pass

enabled convers ion of the spectra l vol tage s ignals to ra-d iance va lues . The da ta f rom th i s exper iment sensor

were furn i shed to the Pr in c ip a l Invest igators in theform of compute r t apes and 16-mm film.

T y p i c a l spec t ra l da ta ob ta ined w i t h t he spec t romete ra re shown in figure A-ll(b). The lower spec t rum was

ob t a i ne d whe n t he Skylab spacecra f t was over W hi teSands, New M exico , on a foggy mo rning . On ly the the r -mal region of the spec t rum is s h o w n . For compar i son ,th e l ine at the top of the f igure s hows th e spec t rummeasured by a s imilar spectrom eter m oun ted in a hel i -copter . The difference between the two is due to energybe ing absorbed in the a tmosphere by ca rbon d iox ide ,ozone, and water vapor . Th e di f fe rences at the variouswave lengths i l lus tra te a tm osph eric effects on d atarecorded above th e a tmosphere .

Multispectral Scanner (SI92) .—Another method of

f o r m i n g a n i m a g e is t h r o u g h a p o i n t - b y - p o i n treconstruct ion of an area that has been scanned by an

opt ical mechanica l s canner . Each poin t actual ly repre-sents th e integrated energy from a smal l area cal led ap ic tu re e lement (p ixe l ) or resolut ion cel l . The size ofthe p ic ture e l ement on the ground i s governed by theopt ical design parameters of the sensor and the he ightof the sa tel l i te . The energy from each pixel is col lectedby an opt ical assembly an d focused on to a detector . Th ede tec tor conver t s th e energy received at each ins tantinto an a nalog electr ical s ignal that c an be am pl if ied andrecorded. The electr ical s ignal varies in direct propor-t ion to the changes in the amount of energy received a tth e detector and t hus ca r r ies inform at ion about changesin the reflect ion or emiss ion of radia t ion from the ob-

jects scanned.The m echanica l movemen t (usua l ly ro ta t ion) of am irror in the opt ica l assemb ly produc es the scan l inespe rpend i cu l ar to the sa tel l i te t rack. As the spacecraft




moves , each l ine is scanned so that successive l ines will

fall exa ctly adjacent to each oth er and a con tinuo usswath of the Ear th can be m a p p ed . Th e scan lines canbe curved or s t r a igh t depend ing on the method chosento generate the scan motion. The qual i ty of the data de-pends on the swath w id th , def ined by the unob s t ruc ted

angle t h r o u g h w h i c h th e s c a n n i n g m i r r o r is designed torotate, and is l imited by changes in the atmospher icpath lengths and in the s ize of the pixel for off-nadir

angles and by the ava ilable elec tr ical ba nd w idt hs fortape recording or telemetry of the image data.

Var iat ions in spacecraf t height or velocity or in mir -ror scan rotat ion can cause an un der la p or over lap of ad-jacent l ines that must be cor rec ted dur in g imagereconstruction at a ground facility. If the height in -creases, as when v iewing the Ear th o b l iquely , the wid thof the area scanned will increase; and, if no change ism a d e in the rotat ional speed of the mir ro r or in the for -ward ve locity of the spacecraf t , ove r lapp ing l ines wil l be

sensed. Fo r contiguous imagery , th e w i d t h of each lineon the ground mus t equa l th e distance th e spacecraf tmoves while scanning each l ine.

By using the proper optical design and an ar ray ofdetectors, a set of coincident spectral bands can be ob-tained for each line. In storing the signals on a multi-band recorder , a mult ispectral set of data is mad e avail-able to the ana lys t fo r in terp re ta t ion . One of the advan-tages of an optical mechanical scanner is that it can col-lect radiation in spectral regions outside as well as coin-c ident with those viewed by a camera, par t ic ular ly in-frared waveleng ths beyond 1 / u r n .Th e par t icular designfo r an optical mechanical scanner used for the E R E P

was called the M ultisp ectra l Scan ner (S192) (fig . A-1 2).This optical elec tromechanical scanner col lec ted in-

com ing radi ant energy using a rotat ing mirror in the im-age p lane to scan th e scene con ica l ly . A spher ical m ir ro rwas the major e lement of a folded reflecting telescopetha t had a 43.2-cm entrance pupil . The energy scannedin th e image plane passed th rough a ref lec t ive Schmidtcorrec tor mirror an d through a field stop that was theentrance s l i t of a pr ism spectrometer . A dic hroic mi rrorthen separated the short wavelengths (0.41 to 2.35 /u.m)from th e long thermal waveleng th band (10.2to 12.5

/ u rn ) . The spectral ly dispersed elec tromagnetic energyreceived from the scene simultaneously ir radiated 13

d e t ec t o r s . E a ch detec to r r esponded to a s p ec i f i cw a v e l e n g t h b a n d a s g i v e n i n t a b l e A-I. T h emultispectral scanner had 22 sc ientif ic data outp uts .O ne sc ientif ic data output (SDO) w as assigned to each

Spherical

relaymirror

O utboard

scan

mirror,

Aspher ic

correctormirror

Spherical primary mirror

D ichro ic beamsplit ter

i Thermal col l imat ing lens

Therm al window

/ Thermal plane

folding mirror

secondary

mirror

Inboard / M onochromatic / /'

scan mirror plane / / !

folding mirror' /' /

M onochromatic col l imat ing lens /

M onochromatic window

(c ) Bar ium f luoride prisms '

Thermal

imaging

lens

M onochromatic

imaging lens

Fused sil ica prism

FIGURE A-12.—Multispectral Scanner (S192). (a) Cutaway

diagram, (b) Scanner optics, (c) Lens system.

352 SKYLAB EREP INVESTIGATIONSSUMMARY



T A B L E A -I.— Detectors and Corresponding W a velength

Bands for the Multispectral Scanner (SI 92)

Detector no .

2

3

4

5

•

7

8

9

10

11

12

13

Band

Color

Viole tVi o le t - b lue

Blue-green

G reen-ye l l ow

Orange-red

Deep red and

in f r a r ed

N e a r in f r a r ed

N e a r in f r a r ed

N e a r inf rared

Near infrared

Mi ddle in f r a r ed

Mid d le inf r a r ed

T h e r m a l i n f ra re d

W avelength, nm

0.41 to 0.460.46 to 0.51

0.52 to 0.56

0.56 to 0.61

0.62 to 0.67

0.68 to 0.76

0.78 to 0.88

0.98 to 1.08

1.09 to 1.19

1.20 to 1.30

1.55 to 1 . 7 5

2.10 to 2.35

10.20 to 12.50

SDO

(or channel)

2218

1 , 2

3, 4

5,6

7, 8

9, 10

19

20

17

11, 12

13, 14

15 , 16 ,

21

detector sampled at 1240 t imes /scan (ban ds 1, 2, 8, 9,

an d 10). Tw o SDO's were ass igned to the detectorssampl ed at 2480 times/sc an (ban ds 3, 4, 5, 6, 7, 11, 12,and 13). Band 1 3 was assigned an addi t iona l redundantS D O .

Each detector produced an electronic s ignal that cor-responded to the average value of the rad ianc e receivedin i ts spectra l ban d from the area on the Earth ' s surfacein t he ins tantaneous FOV o f the in s t rum ent . The de tec -to r outp ut s were am pl i f i ed , conver ted to digi ta l values ,mul t i p l exed , buffered , and recorded on magn e t i c t ape .

The 0 .182-mrad FOV measured by each de tec tor pro-

vided an instantaneous ground coverage of a squarearea 79 m on each s ide. Al th ou gh the scan assembly ro-tated a full 360°, on ly th e f o rward 110° were used to ob-ta in sur face da ta w i th th e ca l ib ra t ion da ta t aken on theremainder of the scan. The corresponding sweep angleviewed f rom th e sensor w as 10.4° , which provided ag r o u n d s w a t h w i d t h of 74 km.

Because the origin al the rm al detector (Y -3) had less

t han spec i f i ed sens i t iv i ty , a more sensi t ive detector(X-5) was ins ta l led in January 1974 during the Skylab4 miss ion . Checkout of t h i s i n s t r um e n t was ac -c om pl is he d J a nu a r y 15 to 17, 1974.

A n e x a m p l e of the mu l t i spec t ra l s canner im agery is

s hown in f igure A-13 , Th e data from t h i s e x pe r i m e n twere furnished to the Principal Investigators in the

form of imagery (from one SDO per detector) and com-p u t e r tapes.

Act ive and Passive M i c r owa ve Sensors

M i c r o w a v e sensors operate in the m i l l i m e t e r tom e t e r region of the e lec t romag ne t i c spec t rum . Becausethe longer wavelengths require larger antennas for a

given angula r reso lu t ion , h igher reso lu t ion microw ave

s p a c e sensors u s u a l l y o p e r a t e a t t h e shorter

w a v e l e n g t h s , w i t h th e except ion of spec ia l appl i ca t ions .An ac t ive m icrow ave sensor t ran sm i t s repe t i t ive

pulsed burs ts of energy tha t are directed in a givendirect ion by t he a n t e nna b e a m . A d i s c o n t i n u i t y , such as

th e a tmosphere / l i t hosphere in te r face , wil l reflect orscatter a pa r t of the energy back to the t ransmi t t ing an -

t enna , where it is accepted by the receiver between th et r ansmi t t ed burs ts . A fte r th e rece iver , w hich is designedto m a t c h th e t ransmi t t ed s ignal cha rac te r i s t ics for op-

t imu m d e tec tion , conver t s the rad iof requenc y energy tovideo frequencies , s ignal process ing is p e r f o r m e d . In

remote-sensing appl icat ions , in which the effect of

ei ther th e Earth ' s surface or the a tmosphere on thet ransmi t t ed ra d ia t io n i s measured , the geo met r i c con-f igurat ion of the observa t ions wil l depend on both th e

target cha rac te r i s ti cs and the rada r sys tem pa ramete rs .Genera l l y , wh en the spa t i a l re so lu t ion depends only onthe antenna s i ze , t he opera t ion i s t e rmed beamwidthl imi t ing and is used to measure the amount of backscat -ter from a given area w i th in the antenna beam (scat -t e romete r ) . To derive a radar signature for each

m e a s u r e m e n t , th e measured backsca t t e r is nor m a l i ze drela t ive to the be am wid th- l im i ted a rea. The resu l t an tradar cross section per un i t area , or backscat ter coeffi -cient , will depend only on the surface characteris t ics ,

the incidence angle , and the polarizat ion for which theva lues were de te rmined .Th e backscat ter coefficients measured by a scat-

terometer are es t imates of the mean return of anoise l ike s ignal . To reduce fluctuations as well as in-crease th e s ignal -to-noise ra t io, a l ong pul se is t ransmi t -ted. For a mono stat ic radar that uses the same tra nsm it -t ing a n d re ce iv ing a n t e n n a , th e t r a n s m i t t e d pu l s e wi d t hc a nno t exceed t h e e x pe c te d r ound - t r i p t r a ve l ti m e(2/?/c, whe r e R is the range and c is the electromagnetic

w a v e p r opa ga t i on s pe e d ) , so t h a t th e received a ndt ransmi t t ed energy wil l n o t in te r fe re . Th e p u l s e w i d t h

used for the Skylab s ca t te romete r w as a p p r o x i m a t e l y 4

mil l iseconds fo r higher incident angles .The active sensor can also be used as an al t imeter to

measure prec i se ly th e spacecraft height rela t ive to thesubsate l l i te groun dt rack . Nar row t ransmi t t ed pul ses a re

E R E P S E N S O R S Y S T E M S 353



B a n d 3

i • . '

B a n d 5

Band 4

Ban d 6

(a )Band 7 Ban d !

FIG U RE A -13 .—Im a g ery from the 13 S192 detectors taken over Las Vegas, Neva da; Lake M ead; the Colorado Ri ve r ; a n d t he Ho o v e r Da m .

(a) Bands 1 to 8. (b) Ba n ds 9 to 13.

3 5 4 S K Y L A B E R E P I N V E S TI G A T IO N S S U M M A R Y



•j . • >

*vi^v>\1MÂ

Ban d 11 Band 12

B a n d 1 3

F I G U R E A-13 .—C onc luded .

used for th i s app l i ca t ion , and the arr iva l t ime of eachpul se re l a tive to the t ransmi t t ed t ime i s measured . T imeprecis ion (1 nanosecond = 15 cm) is eas i ly obtain ed,and a prof i l e of the su bsa te l l i t e grou nd t rack can be ob-tained by plotting a t ime his tory of the altimeterm e a s u r e m e n t s . A t n a d i r , th e spa t i a l re so lu t ion is pul se -wid th l imi ted r a t he r t ha n a n t e nna b e a m wi d t h l i m i t e d

(fig. A -14 ) , if suff ic ien t ly na r r ow t r a ns m i t t e d pu ls e s a reused.

T h e opera t ion of both th e scat terometer and theal t imeter is based on the reflect ive propert ies of a rough

surface. How ever , wh en smooth a reas are e nc oun t e r e d ,th e scat terometer will become inopera t ive at larger inci -dence angles , whereas the a l t imeter , operat ing a t nadir ,wil l be act ivated b y m irror l ike re turns tha t prese rve th etransmitted pulse shape. In this case, the effective area

of reflect ion is reduced to the f i rst Fresnel zone , w hic hmay be on l y a f rac t ion of the pu l s e wi d t h - or b e a m -

wid th - l imi t ed area (fig. A-1 4) . The s ize of the Fresnelzone depends only on the p l a t form he ight and the rada rwave length and thus i s independent of both thepu l sewid th and the antenna s ize .

E R E P S E N S O R S Y S T E M S 35 5





Flight direction P i tch

e , -6 - 4 0 . 1 °6 = 4 8 °

Fl ight di rect ion

16 .695 '

15.6° 31.6 29"

2 9 . 4 ° 4 3 . 4 8 0 "

52.550°

Vtrue incidence angle

Ce l ls

Fl ightpath

(c)

M easurement

cel l

R i g h t

Le fUr i gh t

l l k m

F l i gh t direct ion

I_ . - - - B e a m

J centerl ine

(d )

— M easurement n te rva ls

=185 km

F I G U R E A - 1 6 . — R a d i o m e t e ran d scat terometer data , (a ) In t ra c k n o n co n t i g u o u s sca n n i n g m o de wi th v a r i ed p i t ch a n g l e 8; n is the l o ca l v e r t i ca l

vector, (b ) Crosst rack nonc ont igu ous scan mod e, (c) In t r ack cont igu ous scan mod e, (d) Crosst rack c ont iguous scan mod e.

measured ene rgy , conve r t ed to b r igh tness t empe ra tu re ,was compared to t he mean no i se ene rgy from tw ok n o w n i n t e rna l t empe ra tu re source s fo r ca l ib ra t i on to

yie ld an accura t e p ro po r t iona l meas uremen t o f t hemic rowave emiss ion of t he E a r t h w i t h i n th e a n t e n n ah a l f - p o w e r po in t s .

Th e scat terometer measured th e radiat ion backscat -te r f rom the Ea rth at a center f req uency o f 13 .9 GHz as

a funct ion of incidence angles f rom 0° (ver t ical ) to 48°fo r different p o l a r iz a t i o n c o m b i n a t i o n s an d scanningmodes as shown in f igure A-16. The calculated scat ter -in g coeff ic ient

w asrelated

to theroughness

and thedielectric p rope r t i e s of the surface reflections. Several

measurement s of the scattered r e tu rn s igna l (whichresembles thermal noise) and receiver noise were taken

and in tegrated to obtain an accura t e measurement of

ave rage re tu rn power , f rom which t he backsca t t e r ingcoeff icien t w as calculated. Co ncurre nt operat ion of ther ad iome te r and the scat terometer enabled col lec t ions ofval ues o f t he backsca t t e r ing coe f f i c i en t and apparen tblack-bo d y temperatures for each surface area. Thismethod resul ted in the abi l i ty t o s tudy emiss iv i t yeffects f rom ref lect ivi ty effects in the same area.

An ex am pl e o f r ad iome te r / sca t te rome te r da t a ( i n

two po l ar i za t ions) co l le c ted f rom Hur r i can e Ava of f t hecoast of Mexico is shown in f igure A-17. The winds at

th e closest a p p r o a c h of the S193 sensors to the center ofth e h u r r i c a n e h ad speeds of a p p r o x i m a t e l y 90 k m / h r ,

w i t h 10-m wav e heights . The changes in the b acksc at teras th is spacecraf t passed by the storm were caused bychanges in surface roughness, as s l igh t ly at tenua ted byth e clouds. As the windspeeds increased near th e storm

E R E P S E N S O R S Y S T E M S 357



1 . - Scatterometer VV, HH polarization

—^ R adiometer V, Hpoarization

Incidence angle

Skylab

qroundtrack

F IGU RE A - 1 7 . —Rad iom e t er a n d scat te rometer data f rom H u r r i c a n e A v a . (V = vert i cal t ransmi t ; H = h or i zon t a l t r ans m i t ; V Vtransmit, vert i cal rece ive ; HH = h or i zon t a l transmit, h or i zon t a l rece i v e . )

vert i cal

center , the scattered signal inten sity increased becauseof increased surface roughness. The microwave tem-perature increased because of b o th t h i c k e n in g c louds

and increased roughness. These data were analyzed tod e t e r m i n e t h e f e a s i b i l i t y o f u s i n g t h e p a s s i v em i c r o w a v e data to cor rec t th e rada r data fo r a t t e nua t ionan d t he n de t e r m in ing th e windspeed .

Th e S193 a l t ime te r w as designed to operate in ap reprogramed sequence of approx ima te ly 3 minutes .Each sequence consisted of a data acquisit ion and

system cal ibrat ion subsequence. To increase th e flex-i b i l i t y of the system and to s tudy th e var ious effects ofdif ferent sy s t e m pa r a m e te r s , five different c o m b i n a -t ions of pu l se w id th , r ec e ive r b a ndw id th , and off-nadir

358 S K Y L A B E R E P I N V E S T IG A T I O N S S U M M A R Y



TABLE A -II.— Basic Sequence ofAltimeter Operation

Transmit te r

Step Submode

(a )

Pulsewidrh,

nsec

/Fb

filter Ant e nna

(receiver), angle, deg

MHz

Mode 1 ( pu lse

i

1

2

1

4

5

0

1:

14

-

DAS-1

DAS- 2

D A S - 3

CDS-1

CDS- 2

C D S - 3

UAS-1

D A S - 2

D A S - 3

CDS-1

C D S - 2

C D S - 3

100t o o100

1 0 0100100

M o d e 5

100130

:n20

10

10 0

10

100

100

100

10

10

s h a p e )

Subs a te l l i t e

Subs a le l l i l e

0.431 p i t c h

N A d

N A

N A

No . of

(c )

5061

61

7

5

5

(p u l s e c o m p r e s s i o n )

10

100100

10 01 1 )

Subsate lli te

Subs a te l l i t e

Subs a te l l i t e

N A

N \

N \

16

99

- i

~

1

-

DAS = data acquisition step; CDS -= caibrationdata step.

Intermediate frequency.

cOne frame corresponds to approximatey 1 second of data.

Not applicable.

angle were available . The basic sequence of o p era t io n

fo r modes 1 and 5 , w h i c h w e re most f r equ en t ly u sed inth e a l t i m e t e r o p e r a t i o n , is s h o w n in t ab le A- I I .

A n e x a m p l e of the al t imeter data over an a n o m a l y inthe gravita t ional field of the Ear th is s h o w n in f igures

A-18 and A-19. Because of th i s an o maly , the mean sea

l ev e l d ev ia tes co n s id er ab ly f ro m th e sp h er ica l Ea r th

mo d e l e l l ip so id r ep resen t in g the sh ap e of the E a r t h .These i l lu s t r a t io n s sh o w a 20-m depress ion of m e a n sea

level as o bta in ed d i r ec t ly f ro m th e a l t imete r sensor. Th ea l t imete r measu remen ts co r r e la te wi th in d ep en d en t

measurements of sea level in th is reg ion .

L-Band Radiometer (SI 94).—The objective of the L-

B a n d R a d i o m e t e r was to ev a lu a te th e a p p l i c a b i l i t y of a

p ass iv e micro wav e r ad io mete r to the s tu d y of the Ear thfrom orbita l a l t i tudes . The r ad io mete r measured the

br ig h tn ess temp era tu r e o f th e te r r es t r ia l su r f ace a lo n g

the spacecraf t g roundtrack to a high degree of accu racy .

- 7 . 5 m

Vm

L o n g i t u d e , deg W

Figure A-18.—Skylab 2 groundtrack for altimeter data.

The S194 sensor ( f ig . A-20) h ad a f ixed an te n n a w i tha 3-d B (h a l f p o wer ) beamwid th of 15.0°. The energy

received by th e a n t e n n a w as in teg ra ted a t a r a t e t h a t e n -

sured a m i n i m u m of 80-percent ground coverage over-

lap. Th e r ece iv er p ro v id ed a dig i ta l r ep r esen ta t io n of the0- to 350-K in p u t r ad io m et r ic temp era tu r e r an g e . Th esys tem h ad an in te rn a l ca l ib r a t io n n e tw o rk r e f e ren ced

to a fixed hot- or co ld - lo ad in p u t .

The r a d i o m e t r i c b r i g h t n e s s te m p e r a t u r e was

measured w i t h a reso lu tion of ±1.0 K at a w a v e l e n g t h

o f ap p ro x im ate ly 21 cm. Th e sys tem o p era ted a t a

center f requency of 1 .4125 GHz w ith a ba nd w idt h of 27

MH z . Op era t in g at th i s f r equ en cy , the sensor p ro v id ed

measurements t h a t w e r e m i n i m a l l y a f f e c t e d b ymeteoro logical condit ions .

The 3-d B beamwid th imp l ies th a t 50 p ercen t of the

energy received by the an ten n a w as received in the 15°




1 2 0 r

'

.1 40

Trench area

(large localized

grav i t y

anomaly!'"'

Pass 6

• P uerto R i co

land mass

20 40 60 80

E l a p s e d time, s e c

100 120 '

F I G U R E A - 1 9 . — A l t i m e t e r range measurements. F I G U R E A - 2 0 . — L - B a n d R ad i o m et e r (S194).

by 13.9° sol id p yra m id centered about the ver t ical axis .The antenna received more than 90 percen t of theenergy available in a first-nulls beamwid th (p r imarylobe) that encompassed a swath wid th o f approx ima te ly28 2 km at the 435-km orbital al t i tude, and the s ignaturewas inf luenced by the entire view area. However , thesignature recorded by the facility was inf luenced to amuch larger degree by the br ightness of the mater ia lcon ta ined wi th in the 3 -dB beamwid th : a 111 -km swathcentered about th e nad i r po in t . Data ou tpu t w as eigh-teen 10-bit words/sec. Sensor r ad iomet r ic c a l ib ra t ion

w as acquired by v i ew i n g th e Moon and deep space.

Examples of the data produced by the S194 sensorare shown in f igures A-21 and A-22. The spacecraf tmoved f rom Baja Ca lifornia across th e Gulf of Cal i fo r -nia and on into M exico along the groundtrack show n inthe m ap at the top of figure A-21 . The an tenna foo tp r in tis shown as circles on the f l igh tpa th . Th e solid circlerepresents the half -pow er po int on the antenna pa tternand corresponds to a c ircular area 124 km in d iameter .The f irs t nul l in the antenna pattern is shown by thedashed c irc le representing 285 km in diameter . Th e plotin th e l o w er p o r t i o n of f igure A - 2 1 s h o w s th e

r a d i o m e t e r r e s p o n s e a l o n g t h i s g r o u n d t r a c k .




8 6 2 1659D i s t a n c e , km

2 4 5 6

F I G U R E A-21.—I - B a n d Radiometer data f rom Baja C a l i f o r n i a .

."

:

2 2 0^

£ 200

g. 180

0>

160.

= 1 4 0CTi

™ 1 2 0

100

81

P a c i f i cO c e a n M e x i c o

M easured

C a l c u l a t e d

: 5 5

T i m e , min

• • •

FIGURE A-22.—Brightness temperature plots of data from the L-

Band Radiometer.

Radiometer response is shown in terms of microwavebrightness temperature . The low tempera ture of the seais caused by its low emissivity. Land surfaces haveemissivities approaching that of a black body, so thatthe m icrow ave temperatures for land surfaces are closeto actual temperatures.

Correla tions were obta ined between moisture con-tent of the soil an d radiometr ic data from SI93 andSI94. The correla tions indicate tha t mic rowave sensorsm ay be quite useful for such measurements in the

future .

EREP SENSOR SYSTEMS 36 1






A P P E N D I X B

Skylab E R E P Pr incipal Invest igators '

United States

A L A B A M A

R o b e r t R . J ay roeN A S A George C . M arsh a l l Space F l igh t Cen te rH u n t s v i l l e

A R I Z O N A

George G u m e r m a nPrescott CollegePrescot t

C A L I F O R N I A

M o n e m A b d e l - G a w a dNor th Amer i can Rockwe l l Corpora t ionT h o u s a n d Oaks

D a v i d C . A n d i n gSc ience A pp l i ca t ions , Inc .L a J o l l a

Ir a C . BechtoldBech told S ate l l i te Technology C o.C i t y of Indu s t ry

R . G o r d o n Bent l eyBureau of L a n d M a n a g e m e n tRive r s ide

Robe r t N . Col we l lSchool of Fores t ry and Conse rva t ion

Un iv er s i ty o f Ca l i f o rn iaBerkeley

aThe listed i nves t iga to r s (wi th affiliations s hown) c ompr i s ed th e

ini t ia l a p p r o v e d t e a m fo r E R E P d a t a a n a ly s is . T h r o u g h o u t the in-vest igat ions program, some Principal Inves t iga to r s c hanged a f f i l i a -t ion or adeq ua te da ta were no t ob ta ined to allow some inves t igat ionsto be pe rfo rm ed .

A . Ear l Dav i s

Resource s A gency of Californ ia

Sac ramento

A l e x a n d e r F. H. GoetzN A S A Je t Propu l s ion L abora to ry

PasadenaR o b e r t C . Hel l e r

U S D A / F SPacific Southwes t Forest and R a n g e E x p e r i m e n t

Stat ionBerke ley

Phi l ip G. L ang l eyEar th Sa t e l l i t e Corp ora t ionBerke ley

Dal e F. L e i p p e rD e p a r t m e n t of Oceanography

U.S. Naval Post Graduate School

Monte rey

R o n a l d J . P . L y o nSchool of Earth Sciences

Stanford U n i v e r s i t yStanford

Pau l M. Mer i f i e l dEar th Sc i ence Research C orpora t ion

San ta Monica

Douglas Pi r ieU.S. Engineer Distr ictSan Francisco

Char l e s E . Poul tonEar th Sa t e l l it e Corpo ra t ion

Berkeley

363



C A N A L Z O N E

Jack E. Staples

I n t e r - A m e r i c a n Geodet ic SurveyFort Cl ay ton

C O L O R A D O

Peter M . K u h n

N O A A / E R L / A P C LBo u ld er

K e e n a n L eeColorado School of MinesGolden

Roger B . Morr i son

U.S.G.S.D e n v e r

H a r r y SmedesU.S.G.S.

D e n v e r

K e n n e t h W a t s o nU.S.G.S.D e n v e r

D E L A W A R E

Vytau tas Kl emasCollege of Ma r ine S tud iesUnive r s i t y o f De l awareN e w a r k

Karl -Heinz Szekie ldaCollege of Marine StudiesUnive r s i t y o f De l awareN e w a r k

DISTRICT OF C O L U M B I A

Robe r t H . Al exande rU.S.G.S.W a s h i n gt o n

J o h n C . Al i shouseN O A A / N E S SW a s h in g to n

R i c h a r d R . A n d e r s o n

D epar tm en t o f B io logyTh e A m e r i c a n U n i v e r s i tyW a s h in g t on

James P. Hol l inge r

M i c r o w a v e Rem ote S ensing Sect ionU.S. Nav al Research L abora to ryW a s h i n g to n

A l l a n S h a p i r o

U.S . Na val Research L ab ora to ryW a s h i n g t o n

DavidS . S imone t tEar th Sa t e l l it e Corpora t ion

W a s h i n g t o n

F L O R I D A

J o h n W . H a n n a hBrev ard C o u n t y P l a n n i n g D e p a r t m e n tTi tus v i l l e

Aaron L . HigerU.S.G.S.

M i a m i

George A . M a u lN O A A / A O M L

M i a m i

D u n c a n RossN O A A / A O M LM i a m i

IL L INOIS

R a v i n d e r K. J a inU.S. A.C.E.C h a m p a i g n

I N D I A N A

Roger M . Hoffe rL A R SPurdue Unive r s i t yW e s t L a f a y e t t e

L e R o y F. SilvaL A R SP u r d u e U n i v e r s i tyWes t L afaye t t e

Charles Wier

Dep ar tmen t o f Natu ra l ResourcesI n d i a n a Geological SurveyBl ooming ton

364 S K Y L A B E R E P I N V E S T IG A T I O N S S U M M A R Y



I O W A

R i c h a r d H o p p i nD e pa r t m e n t of GeologyTh e U n i v e r s i t y of IowaIowa City

K A N S A S

J . R. E a g l e m a nU n i v e r s i t y of K a ns a s / C R I N CL a w r e n c e

R. K. MooreU n i v e r s i t y of K a n s a s / C R I N CL a w r e n c e

Harold L . YargerKansas Geological Su rveyU n i v e r s i t y of Ka nsa sL a wr e nc e

LOUISIANA

Rober t H. C a r t m i l lN A S A E a r th Resources Labora torySlidell C om pu t e r C om pl e xSlidell

M A I N E

Ernes t G. StoeckelerM aine S ta te Highwa y Comm issionBangor

M A R Y L A N D

Rona ld BrooksW ol f Research & Deve lopm ent Corpora t ionR i v e r d a l e

Morton Ke l l e rN O A A / N O SRockv i l l e

C . Lawrence KorbNA SA Goddard Space F l ight Cente rGreenbe l t

W i ll i a m E. Shenk

Meteorology BranchN A S A Godda r d Space Fl ight Ce n te rGreenbe l t

R. Lawrence SwansonN O A A / N O SR o c k v i l l e

K . M . W e a ve rM a r y l a n d Geological Survey

T h e J ohns H opk i ns U n i ve r s i t yBal t imore

MASSACHUSETTS

J a m e s C . BarnesE n v i r o n m e n t a l Research & Technology , Inc .Lex ington

D a v i d T. C ha ngE n v i r o n m e n t a l Research & Technology , Inc .Lex ington

Saul CooperReservoir Control CenterU .S .A .C.E .N ew England Divis ionW a l t h a m

H . T . U . Smi thDepartment of GeologyUnivers i ty of Massachuset tsA m he r s t

M I C H I G A N

J . B r a i t hwa i t eEnvironmental Research Ins t i tute of Michigan

A n n A r b or

Rober t Horva thEnvi ronmenta l Resea rch Ins t i tu te o f MichiganA n n A r b o r

Lester V . Mandersche idDepar tment of A gr icu l tu ra l EconomicsM ichigan S tate Un ivers i tyEast Lans ing

R i c ha r d F. N a l e p k aEnv i ronm enta l Resea rch Ins ti tu te of MichiganA n n A r b o r

Fabian C . PolcynEnv i ronm enta l Resea rch Ins t i tu te of M ichigan

A n n A r b o r

S K Y L A B E R E P P R I N C I P A L I N V E S T I G A T O R S 365



I rv in J . Sat t ingerEnv i ronm enta l Research Ins t i t u t e o f M ich iganA n n A r b o r

Frede r i ck J . T h o m s o nE n v i r o n m e n t a l Research Ins t i t u t e o f M ich iganA n n A r b o r

R o b e r t E . T u r n e rEnv i ro nm enta l R esearch Ins t i t u t e o f M ich iganA n n A r b o r

R o b e rt K . V i n c e n tE n v i r o n m e n t a l R e s e ar c h I n s t i t u t e o f M i c h i g a nA n n A r b o r

MISSISSIPPI

Char l e s W . Bouch i l l onIn s t i tu te o f E n v i r o n m e n t a l S t u d ie sMiss is s ip p i S t a te U n i v e r s i t y

State CollegeW i l l i a m H . StevensonN a t i o n a l Marine Fisher ies ServiceNA SA Na t iona l Space Techno l ogy L abora to r i e sBay St. Louis

N E V A D A

Jack Q u a d eM a c k a y School of M i n e sUnive r s i t y of Nevada

R e n o

N E W HAMPSHIRE

R i c h a r d E. StoiberD e p a r t m e n t of E a r t h SciencesDar tmouth Co l l egeHanove r

N E W Y O R K

Ernes t E . H a r d yN ew York State College of A g r i c u l t u r eCorne l l Un ive r s i t yI thaca

W i l l i a m Har t ing

Tri State Trans portat ion Com missionN ew Y o r k

K enne th R . Pi ech

C a l s p a n , I n c .

Buffalo

W i l l a r d J . Pierson, J r .

C U N Y I n s t i t u t e f o r M a r i n e a n d A t m o s p h e r i cSciences

Th e C i ty CollegeN ew Y o r k

E d w a r d Yost

Science Eng ineer in g Research GroupC . W . Post Cente rL o n g I s la n d U n i v e r s i t y

Greenval e

N O R T H C A R O L I N A

Lee S. Mil l e r

En g in eer in g & Env i ronm enta l Sc iences Div i s ion

Research Tr i ang l e Ins t i t u t eResearch T riangle Park

Char l e s W . W e l b yNo r th C aro l ina S ta t e Un ive r s i t yRaleigh

N O R T H D A K O T A

H arv ey K. Ne l sonBureau of Sport Fisher ies and Wild l i fe

No r the rn P ra i r i e W i l d l i f e Research Cen te rJ a m e s t o w n

OHIO

A . G . M o u r a dBatte l le M e m o r i a l I n s t i tu t eCol umbus L abora to r i e sC o l u m b u s

David C . SweetO h i o Sta te Depa r tmen t of Deve l opmentC o l u m b u s

O K L A H O M A

Rober t J .Co l l i ns , J r .

Eason Oi l Com panyO k l a h o m a C i ty




P E N N S Y L V A N I A

George J . M c M u r t r yOffice fo r Remote Sens ing of Ear th ResourcesThe P e nns y l va n i a S ta te U n i ve r s i t yU n i v e r s i t y P a r k

SOUTH C A R O L I N A

N . K . OlsonD i v i s i o n of GeologySouth Carol ina S ta te Dev e lopm ent BoardC o l u m b i a

SOUTH D A K O T A

Vic to r I . M y e r sR e m ot e S e ns ing I n s t i t u t eSouth Dak ota S ta te Un ivers i tyBrook ings

T E N N E S S E E

Gera ld K . MooreU.S.G.S.N a s h v i l l e

TE X A S

Vic to r R . BakerDepartment of Geological SciencesThe Un iver s i ty of Texas a t Au s t inA u s t i n

T h o m a s L . B a r ne t t

NA SA L ynd on B . John son Space Cente rHous ton

R . B r y a n E rbNA SA L ynd on B . Johnson Space Cente rHous ton

W i l l i a m G . Har tU S D A / A R SCitrus Insects ResearchW eslaco

H arbh a jan S . H a y r eD e pa r t m e n t of Elec t r i ca l Engineer ingW ave Propaga t ion Labo ra tor ies

Unive r s i t y of HoustonHous ton

D a v i d E. Pi t tsN A S A L y n d o n B . J o h n s o n Space C ente rH o u s t o n

J a m e s V . A . T r u m b u l lU.S.G.S.

U n i v e r s i t y of Corpus Chr i s t iC o r pus C h r i s t i

Cra ig L . W i e g a n dU S D A

R io Grande Soil & W ater Resea rch Cente rW es laco

U TA H

M . L . JensenD e pa r t m e n t of Geological & Geophysical SciencesUnive r s i t y of U t a hSalt Lake Ci ty

VI R G I N I A

A l d e n P. ColvocoressesU.S.G.S.M c L e a n

W i l l i a m J . Hargis , J r.V irg in ia I n s t i t u t e of M arine Sc ienceGloucester Point

W i l l i a m J. KoscoU.S.G.S.M c L e a n

Harold G. M arsha l lD e p a r t m e n t of Biology

O ld D om i n i on U n i ve r s i tyNo r f o lk

J ohn D . M c L a ur i nJames W . S c hoonm a k e r , J r .U.S.G.S.M c L e a n

Joseph T. Pi loneroU.S.G.S.M c L e a n

Doyle G . Smi th

U.S.G.S.M c L e a n

S K Y L A B EREP PRINCIPAL INVESTIGATORS 367



W A S H I N G T O N W I S C O N S I N

W i l li am J . Cam pbe l lU.S.G.S.

Universi ty of Puget SoundT a c o m a

Troy A . Cr i t e sKe n t Jun io r High Schoo l

K e n t

D a v i d L . TingeyBoeing Space C enterTh e Boe ing Company

K e n t

Joseph B . Zmol ekL ourdes High SchoolOshkosh

W Y O M I N G

Robert S. HoustonD epar tm en t o f Geo l ogyU n i v e r s i t y o f W y o m i n gL a r a m i e

In terna t iona l

A R G E N T I N A

O . D o m i n q u e zIns t i t u t e N ac iona l de Technobg ia Agropecuar raBuenos Aires

E d u a r d o J . M e t h o lDireccion Nacional d e Geologia y M i n e r i aBuenos Aires

Rod o l fo L iendo Sou l aDireccion General d e Fabricaciones Mil i taresBuenos Aires

A U S T R A L I A

N . H . FisherBureau of M i n e r a l Resources , Geology and GeophysicsCanbe r ra C i ty

B O L I V I A

Car l os BrockmannDirector, Servicio Geologico de Bol iviaLa Paz

B R A Z I L

L ui s Henr ique d e Azevedo

Beri lo L ange rM i n i s t r y of Mines and EnergyD N P M - P r oj ec t R A D A MR io d e J ane i ro

F e r n a n d o d e M e n d o n c aIn s t i tu te de Pesqu isas Espa c i a i s ( IN PE )Sao Jose d o s C a m p o sSao Paulo

C A N A D A

R . A . S t e w a r t

To p o g rap h ica l Survey Di rec to ra t eSurveys & M a p p i n g B r a n chD e p a r t m e n t of Ene rgy , Mines a nd ResourcesOt t awa, Ontar io

K. P. B. T h o m s o nCanada Cen t re fo r In l and W ate r sBur l ing ton , Ontar io

C H I L E

Hector Inost rozaR e i n a ld o A l d u n a t eI n s t i t u t e Hidrograf ico de la ArmadaValp a ra i so

E N G L A N DP. G . M o t tH u n t i n g Surveys L td .Boreham W o o d , Hertfordshi re




R . M . S h a c k l e t o nResearch Inst i tute of Afr ican GeologyU n i v e r s i t y of Leeds

Leeds

J . L . Van Genderen

D e p a r t m e n t of Geography

The U nive r s i t y o f Sheffie ld

Sheffield

F E D E R A L R E P U B L I C O F G E R M A N Y

Dei t er Bann e r tGeological Su rvey of the Fede ra l Repub l i c of G e r m a n yH a n n o v e r

J . B o d e c h t e lIn s t i tu t f u r Al l geme ine u n d M i n e r a l o g i e

d er Unive r s i t a t Ml inchenMi inchen

Kl aus GiessnerGeographisches Inst i tutUnive r s i t y of TechnologyH a n n o v e r

Peter Kronberg

Geologisches Inst i tutTechn i sche Unive r s i t a t C l aus tha lZellerfield

Franz K . L i s tFree U n i v e r s i t y of Berl in

L ehrs tuh l fu r Angewandte GeologicBer l in

G u n t h e r S t u c k m a n n

Geograph isches Ins t i t u tUnive r s i t y of TechnologyH a n n o v e r

F R A N C E

Jacques Gui l lemot

Inst i tu te Francois d u Petrole

R u e i l - M a l m a i s o nM . Vi l l ev i e i l l eBureau d 'Etudes Meteorologie Spat iales

Par is

I N D I A

P . R . Pi sharo tyInd ian Space Research Org an iza t ionPhys i ca l R e s e a r c h L a b o r a t o r yA h m a d a b a d

I R A N

K . Ebtehad jThe Pl an Budge t Organ iza t ionTehran

I S R A E L

Joseph J . O t t e r m a nTel Aviv Unive r s i t y

D e p a r t m e n t of Envi ronmenta l Sc i encesR a m a t A v i v

ITAL Y

Roberto CassinisGeolabMi l an

O . E . F i s c h n i c hFood and Ag r i cu l tu ra l Organ iza t ion

R o m e

Att i l io Moret t i

Servizio Geologico d ' l tal ia

R o m e

J A P A N

T a k a k a z u M a r u y a s uInst i tute of Ind ust r ia l ScienceUn ive r s i t y o f Tokyo

Tokyo

Kiyosh i Tsuch iyaForecast Div i s ionJapan Meteorological Agency

Tokyo

K a n t a r o W a t a n a b eKyoto Gakuen Unive r s i t y

c /o Kobe M ar ine Obse rva to ry

Kobe

S K Y L A B E R E P P R I N C I P A L I N V E S T I G A T O R S 369



M A L A Y S I A

J . B . AhmadGeological Survey of Mal ays i aIpoh

M A L IM a m a d u K o n a t eD e p a r t m e n t of M i n e s and GeologyM i n i s t r y of Indu s t r i a l Deve l opm ent and Pub l i c W o r k sK o u l o u b a , B a m a k o

M E X I C O

Francisco ArzateM i n i s t r y of Pub l i c W orksMexico Ci ty

Luis D el Cast i l l oUniv . Nal . Au t . d e Mexico

I n s t i t u t e d e Geofisica d e E x p l o r a c i o nCiudad Unive r s i t a r i a

Carlos Acosta D e l C a m p oConsejo de Recursos NaturalesN o RenovablesMexico 7, D.F.

Nico l as Sanchez DuronDireccion General d e Agricul turaBaldera

Jose Amando Diez PerezSecretaria d e Recursos Hidraul icosPisco

Ar tu ro Gonza l ez Sa l azarComision Federal de El ec t r i c i dadPisco

Carlos Castil lo TejeroInst i tuto Mexicano de l Pet roleoMexico 14, D.F.

Jorge F. VacaCom is ion de Es tud ios de l Te r i to r io Nac iona l

Secretaria de la Pres idenc i aS a n A n t o n i o

N E T H E R L A N D S

H. E. C. van der M e e r M o h rIn te rn a t io n a l Ins t i t u t e fo r Aerial Survey an d Ear th

Sciences ( ITC )E n s c h e d e

S W I T Z E R L A N D

Haro l d Hae fne r

Un iv er s i ty o f ZUr ic hZ u r ich

T H A I L A N D

Prad i s th Cheosaku lN a t i o n a l Research Counc i lBangkok

V E N E Z U E L A

Jose An ton io Gal av is

Ch ief , M arin e Geology D ivisionMinis t ry of Mines and Hydroc arbonsCentro Simon Bol tvar

Caracas




A P P E N D I X C

Photograph Index

Skylab E a r t h Resources Exper iment Package (EREP) photographs c i t edin th e disc ipl ine s u m m a r y sec t ions are listed by geographic areas.R e pr oduc t i on of the photographs can be obta ined from th e E a r t hResources Observa t ion S ys t ems (E R O S ) D a t a C en t e r , Sioux Falls, SouthDakota 57198.

Geographic

location

Photograph no . EROS Data Center

identification no.

Figure no .

A f r i ca

M a u r i t a n i a SL3-84-360 G30A843600000 5-23

A si a

J a p a n SL4-89-398

A i r c r a f t

G40B893980000 5-27

5-26

A t la n t i c Oc ean

P u er to R ic o SL2-81-240

S192

G20B812400000 5-30

5 -1 2 (a )

E u r o p e

France

Sicily

SL3-34-321

SL3-87-355

G30A343210000

G30B873550000

4-14

4-18

M o o n a n d E a r t h l i m b

M o o n a n d E a r t h

l i m b

E a r t h l i m b

SL3-1 19-2253

SL3-1 19-2254

SL3-1 19-2255

SL4-200-7639

SL4-200-7640

SL4-200-7641

SL4-200-7642

SL4-200-7643

SL4-200-7644

SL4-200-7645

SL4-200-7646

SL4-200-7647

G3701 19225300

G3701 19225400

G3701 19225500

G470200763900

G470200764000

G470200764100

G470200764200

G470200764300

G470200764400

G470200764500

G470200764600

G470200764700

5-33 , upper f r a m e

5-33 , center f rame

5-33, l o w er f r a m e

5-34(a) , f rame 1

5-34(a) , f rame 2

5-34(a) , f rame 3

5-34(a) , f rame 4

5-34(a) , f r am e 5

5-34(a) , f rame 6

5-34(a) , f rame 7

5-34(a), f r a m e 8

5-34(a) , f rame 9

371



Geographic

location

E a r t h l i m b

Photograph no.

Moon an d

SL4-200-7648

SL4-195-7315

SL4-195-7316

SL4-195-7317

SL4- 195-73 18

SL4-1 95-73 19

SL4-52-388

EROS Data Center

identification no.

E a r t h l i m b

G470200764800

G470195731500

G470195731600

G470195731700

G470195731800

G470195731900

G40A5 23880000

Figure no .

5 - 3 4( a ) , f r a m e

5 -34 (b ) , f r a m e

5-34(b) , f r ame

5 - 3 4( b ) , f r a m e

5-34(b) , f r ame

5 - 3 4( b ) , f r a m e

5-35

10

1

;-

4;

N or t h A m e r i ca

Great L a ke s Re g i on

C a n a d a

SL3-40-016

SL4-93-041

SL4-69-058

SL4-140-4215

SL4-1 40-42 16

SL4-14M321

SL4-141-4327

SL4-141-4331

SL4-141-4366

S L A Ra

"RC8-70-061bRC8-70-044

"RC8-70-050

SI 92

G30A4001 60000

G40B9304 10000

G40A690580000

G4701 4042 1500

G470140421600

G470141432100

G470141432700

G470141433100

G470141436600

—625900700, roll 61

625900700, ro l l 44

625900700, roll 50

—

4-21 (a) , 4 -2 l(b)

5-14(b)

5-14(a )

5 -1 6 (a )

5- 1 7(a)5 - 16 ( b )

5 -1 7 (b )

5-15

5- 1 7(c)5-19

5-20(b)

5-20(c)

5 - 20( d )

6-41

S out h A m e r i ca

A r g e n t i n a

Braz i l

A l a b a m a

A r i zona

SL3-34-165

SL3-33-162

SL3-33-093

SL3-83-361

U n i t e d

SL4-93-152

S192

SL4-90-305

SL3-86-01 1

SL4-92-356SL4-93-057

SI 90 A

SI 92

SL4-90-306

S192

SL4-94-237

S-74-23477

(S192)

G30A341650000

G30A331620000

G30A330930000

G30B833610000

States

G40B931520000

—

G40B903050000

G30B8601 10000

G40B923560000

G40B930570000

—

—G40B903060000

—G40B942370000

—

3-6(a)

4-26(a )

3-5(a)

3-2(a)

2-17

5-43

2-29(a)

2 - 7 ( a ) , 6 - 5

A-7(b)

A -7 (d )

6 -35 (b )

6-35(c )

4-84-10(a), 4-10(b)

4-19(b)

6-13

aSide-looking a i r b o r n e r a d a r .




Geographic

location

Photograph no. ER OS Data Center

identification no.

Figure no.

U n i t e d States

Cali fornia

Colorado

Connect icut

Florida

Georgia

I n d i a n a

SL2-04-121

SL2-03-121S192

SL3-87-111

SL4-92-333

SL4-78-071

SL4-77-071

S-73-1227

SL4-92-336

S192

SL4-92-351

S192

SL4-94-013cS-75-31982

SL4-76-078

SL4-92-335

S192

S192SL4-92-349

SL4-92-351

A i rc r a f t

SL4-77-071

SL4-78-069

N O A A - 3 im a g e

SL2-09-017

SL3-21-331

SL3-2 1-004

A i rc r a f t

A i r c r a f t

A i r c r a f t

A i rc r a f t

SL2-8 1-020

SL2-15-010SL2- 15-009

S192

SL2-10-016

S192

S192

S192

S192

S192

SL3-88-276

SL3-88-141

SL4-90-046

S192

G20A041210000

G20A031210000

—G30B 871 110000

G40B923330000

G40A780710000

G40A770710000—

G40B923360000

—G40B9235 10000

—G40B940 130000

—

G40A760780000

G40B923350000—

—G40B923490000

G40B9235 10000—

G40A770710000

G40A780690000

—

G20A09 01 70000

G30A213310000

G30A2 10040000————

G20B8 10200000

G20A 1501 00000G 20A 150090000

—G20 A 100 160000

————

—

G30B882760000

G30B881410000

G40B900460000

—

3-3(a)

3-3(b)3-4

4-66-15

6 -1 7 (a )

6 -1 7 (b )

6-1

6-20(a)

6-36

6-27(a )

6-27(b)

4-ll(a),

4-1 l ( c )

4- 15( a ) ,

4-1 7 (a ) ,

4- 1 7(c)

4-23(a) ,4-24(a)

4-25(a )

4-25(b)

5-28

5-21

5-22

2- 1 (a )

2-1 (b)

3-7(a)

3-9(a)

3 -9(b)

3-9(c)

3 -9 (d )

3-8 (c)

3-8(a )3-8(b)

3 -8(d)

4-22(a) ,

4-22 (c )

3-13

2-12(a )

6-31

6 -32 (a ) ,

2- 8 ( a )

A- 10( b )

3-11

2-11

4- 1 l ( b )

4-15(b)

4- 17 ( b )

4-23(b)

4-22 (b )

6-32(b)

G ro u n d c a m e r a .

PHOTOGRAPH I N D E X 373



Geographic

location

K e n t u c k y

L oui s i a na

M a r y l a n d

M i s s i s s i pp i

N e b r a s k a

N e v a d a

N e w J e r s e y

N e w Y o r k

N o r t h D a k o t a

O h i o

Photograph no .

U n i t e d

SL4-90-032

SL3-83-056

SL3-22-120

S192

SL2-15-174

SL3-39-123

SL3-83-166

SL3-83-166

SL3-15-172

SL4-92-295

S-73-1510 (S192)

S-73-2839

SL3-25-059

SL3-26-059

SL3-27-059

SL3-28-059

SL3-29-059

SL3-30-059

S192

S192

SL3-28-057

S192

SL3-86-303

SI 90 A

SL3-88-274

SL3-87-300

SI 90 A

S192

A i r c r a f t

S190B

EROS Data Center

identification no .

States

G40B900320000

G30B830560000

G30A221200000

—

G20A 15 1 740000

G30A391230000

G30B83 1660000

G30B8 3 1660000

G 3 0A1 51 720000

G40B922950000

—

—

G30A250590000

G30A260590000

G30A270590000

G30A280590000

G30A290590000

G30A300590000

——

G30A280570000

—

G30B863030000

—

G30B882740000

G30B873000000

—

—

—

—

Figure no .

2- 18 ( a ) , 2-18(b)

6-34(b)

6-34(a)

6-34(c)

2-20(a)

2-20(b)

2 - 13 ( a )

2-3(a )

2-3(b)

2-6

6-10

6-11

A - 9 , s ta t ion 1

A - 9 , s t a t i o n 2

A-9, s ta t ion 3

A- 9 , s t a t io n 4

A - 9 , s t a t io n 5

A - 9 , s t a t i o n 6

A- 1 3

4 -9 (a ) , 4- 9 ( b )

4- 12( a )

4-16

2-21 (a )

2-5(a) , 2-5(b)

2-2(a )

2-2(b)

6-21

2-22

6-19(a)

6-19(b)

374 S K Y L A B E R E P I N V E S TI G A TI O N S S U M M A R Y



Geographic

location

Photograph no. EROS Data Center

identification no .

Figure no .

U ni t e d States

O k l a h o m a

S out h Da ko t a

Texas

U t a h

W y o m i n g

S I 9 1 e ng i ne e r i ng

i n s t r u m e n t

S 1 9 2 e ng i ne e r i ng

i n s t r u m e n t

E R E P sensors

S190 engineer ing

i n s t r u m e n t

S 1 9 3 e ng i ne e r i ng

i n s t r u m e n t

SI 9 4 e ng i ne e r i ng

i n s t r u m e n t

E R E P sensor coverage

SL4-90-144

SL2-08-113

SL2-09-121

SL2-81-316

SL4-94-111

SL4-93-326

SL4-91-005

A i rc r a f t

SL3-83-300

S192

SL2-81-016

SL2-10-010

SL3-88-018

SL2-82-146

S k y l a b a n d

—

—

SL3-1 14-1659

S-72-44415

S-72-44416

—

—

S-73-005-S

G40B901440000

G20A08 11 30000

G20A091210000

G20B813160000

G40B941 110000

G40B933260000

G40B9 10050000

G30B833000000

G20B810160000

G20 A 100 100000

G30B8801 80000

G20B821460000

e n g i n ee r in g p h o t o g r a p h s

—

—

G3701 14165900

—

—

—

—

4-13(a )

4 -5 (a )

4-5 (b)

4-20(b)

2 - 2 5 ( a )

3 - l ( a )

3-1 (b)

3-1 (c)

2-19

6-18

4-1 (a)

4-2 (a)

4-3(a)

4-4(a)

A - l l ( a )

A -1 2 (b )

A - l

A -8 (a )

A -8 (b )

A- 15

A- 20

1-3, A-3

PHOTOGRAPH I N D E X 375






A P P E N D I X D

Principles of Photographic and D igital D ata A nalysis

In t h i s a p p e n d i x , th e m e t h o d s and te rms most com-

m o n l y used in the analysis of photographs and images 'and in the preprocessing and a n a l y z i n g of mul t i spec t r a lscanner digi tal data are discussed. The analysis of

microwa ve da t a r equ i re s h igh l y spec i al ized t e chn iques ;t h e r e f o r e , d e t a i l e d d i s c u s s i o n o f p r o c e d u r e s a n dmeth ods for analyz ing such d ata i s contained insection 6.

Fundam enta ls of Photograph ic Interpre tat ion

ROBER T N. COL WELL"

Photograph i c i n t e rp re t a t i on invo l ves th e systemat ice x a m i n a t i o n o f n e g a t i v e o r p o s i t i v e p r i n t s a n dt ransparencies for the purpose of i d en t i fy in g objectsand judg ing t he i r cond i t ion or signif icance . This processrequ i re s p l ann ing a sequence of ac t ivi t ies which in-c l udes de f in ing t he da t a geom e t ry , enhanc ing t he da t a ,ident ify ing t he d a t a charac t e r i s t ic s , and in t e rp re t ing t heresults.

P H O T O G R A P H I C G E O M E T R Y

The first step in pho to in t e rp re t a t i on is to establish

th e method of acqu i r ing th e data and i ts signif icance inreference to a se t of kno wn features or re lat ionsh ips. Bythis m ea n s , th e i n t e rp re t e r can define th e general pro-port ional perspect ive of features on the pho tograph andcan form a standard for measurement of specif ic ob-jects.

Posit ive prints an d t ransparencies ar e often referred to as "im-ages." In th i s report , "image" or " i m age ry" is def ined as a p r i n t or at ransparen cy generated f rom e lect ronic data ( i .e ., mu lt i spec t ral scan-ner ) .

aUni ve r s i t y o f Ca l i fo rn i a a t B e rke le y .

Th e geome t r i c r e l a t i onsh ips a m o n g film negat ive ,camera lens, and target for ver t ical photographs are i l -lust rated in f igure D-l . Three p r i n c i p a l points thatde f ine th e pos i t i ons a, b , and co n the film correspond to

Image plane

Feature p lane

F IGURE D-l .—Diagram i llustrating th e imaging of ground object s

in vert i cal aer i a l photographs .

377



points A, B, and Con the imaged surface. The perpen-dicular distance / from the camera lens to the film is

the focal length of the camera.Th e scale S is the r e la t ionsh ip be tween a distance on

th e pho tograph and the corresponding dis tance on theground. For example, in figure D- l ,

abS = A B

( D l )

The larger th e d en o m i n a t o r of the f r ac t ion , th esmaller is the scale of the photograph. Th e scale of thephotograph can also be determined f rom the relat ion-ship between th e camera focal length /and th e cameraa l t i tude / / a t th e ins tan t o f pho tography . Then ,

(D2)

Fo r example , th e scale of the or iginal film image ofthe Skylab Earth Terrain Camera (S190B) with a 45.7-cm focal length, taken at a spacecraft altitude of 435 km,is

0.457or

1

435 000 951 860

This f rac t ion indicates that one measurement unit onth e photograph corresponds to 951 860 of the sameuni t s on the ground. Thus , th e scale of the photograph

is approximately 1:950 000.

PHOTOINTERPRETATIVE EQUIPMENT

Photo in terp re ter s use equ ipment fo r three generalpurposes: vie wing , measur ing, and t ransferr ing orrecording detai l . Measur ing instruments may be usedon single photographs or stereoscopic pa irs. Vie win gequ ipment is used to increase th e interpreter ' s abil i ty toscan or study photographs. Some of these ins t rumentsprovid e a s tereoscopic ( three dime nsional) v iew ofover lapping photographs under var ious magnif icat ions,whereas others provide only a two-dimensional butmagnif ied view of objects on photographs. Light tablesaid the photointerpreter in screening and selec t ingphotographs, judg ing the im por tance or qual i ty of thepho tographs , an d examining transparencies or nega-

t ives. The stereoscope, a b inocular viewing instrume ntthat through a combination of lenses, mirrors , andpr isms provides a three-dimensional view of photo-graphs, is one of the mos t im por tan t ins t ruments usedin p h o t o i n t e r p r e t a t i o n . The stereoscopic pr inciple is

used in measur ing and p lo t t in g ins t rumen ts tha t aredesigned p r imar i ly fo r viewing pho tographs and /o r im -ages generated from mu ltisp ect ral scanners (e.g., SI92)or en h a n c em en t of pho tographs . Measurement is alsodone with a hand lens on w h i c h a scale has been etched.Var ious ruler - type and cal ip er - ty pe scales are also used.To transfer inform atio n f rom the photograp h to a basemap or descriptive chart, optical and mechanicaldevices are used. In many Ear th Resources Exper imentPackage (EREP) exper iments , zoom transfer scopeswere used to opt ical ly converge the scale of the photo-

graph with that of the base map. Optical devices wereused to enlarge or reduce the ph otograph s and aid in thetransfer of data. Propor t ional dividers and pantographscan also be used to transfer small amounts of detailedinformat ion .

PHOTOGRAPH E N H A N C E M E N T

Enhancement devices ar e equal ly as useful on photo-graphic and elec tronical ly derived images fo r increasingthe amount of information that can be interpreted bythe analyst . Forms of enhancement inc lude density s l ic -ing, color coding, and co mbin ing m ult ip le images into as ingle composite. Some analysts advocate the use ofmul t ip l e lantern-slide projectors or other optical devices

fo r this purpose, whereas others prefer electronicdevices such as closed-circuit television equipment. Acom bina t ion of op t ica l and e lec t ron ic dev ices i sespecially useful when several mult idate or mult ibandimages of the same area, each containing dif ferent in-formation, are available.

In addit ion to the advantages common to both opti-cal and elec tronic enhancem ent techniques, some im -por tan t relat ive advantages and l imita t ions are associ-ated with each technique. Generally, optical enhance-ment methods and techniques provide better spatialresolution (i .e ., h igher d ef ini t io n) and enable the use ofs impler an d less costly equipment. However, electronicmethods an d techniques offer advantages based onthe i r capabil i ty to quickly selec t and m athe matic al ly ex-pand da ta , to assign color hues, to combine mul t ida teand mu lt iban d data for analy sis , and to geome tr ical lycorrec t an image or a photograph.

3 7 8 S K Y L A B E R EP I N V E S T I G A TI O N S S U M M A R Y



PHOTOGRAPH C H A R A C T E R I S T I C S

The sy nop t i c v i ew of Ear th p rov ided by space pho to -g raphs r equ i re s th e a n a l y s t to revise h is concepts of thesignif icance of shape , s ize , shadow, tone , color , texture ,and pat tern character ist ics of objects in the image. Asan exam pl e , mu ch of t he ER E P da t a cons i st s o f ve r t i ca lp h o t o g r a p h s cove r ing in excess of 26 000 km 2 of theEar th su r face . From th i s new pe rspec t ive , some

features assume greater importance in space photo-g raphs t han in t he g round v i ew and de t a i l s t ha t mayp r e d o m i n a t e i n t he g round v i ew may be near l y i n -dist inguishable f rom space .

The s h a p e of an object as seen in the plan viewp o r t r a y e d by a ve r t ica l pho tog raph p rov ides an impo r -t an t and sometimes conclusive indicat ion of i t s s t ruc-ture, compos i t i on , and f u n c t i o n . For e x a m p l e , in thever t ical view of a forest , it s economic an d recreat ionalva l ue may be ap paren t . The ve r t i ca l v i ew of a l and form

may show effects of tec tonic and erosional processes.

To the motorist , a clover leaf intersect ion is an in-comprehens ib l e maze ; to the ana l ys t , howeve r , th eform and func t ion of the intersection are clear ly evi -den t . Shape is val uab l e to the in terpre ter because it es-tabl ishes th e class of objects to w h i c h an u n k n o w n ob-jec t must be long; shape f req uen t ly enables a conc l us iveid en t i f ica t io n , and i t aids in the u n d e r s t a n d i n g of sig-nif icance and funct ion of the object .

The size of an object is one of the most useful c luesto i t s i den t i t y . By measur ing an unknown ob jec t on ap h o t o g r a p h , th e i n t e rp re t e r c an e l imina t e f rom con-siderat ion groups of features or phenomena. Size can

also be used to f o r m u l a t e sets of possib le inferences thatm a y h e l p to i d e n t i f y s i g n i f i c a n c e . F o r e x a m p l e ,measurement o f the l eng th o f a runw ay can ind i ca t ew h e t h e r or not an airfield can accommodate l a rge je taircraf t .

Shadow in ve r t i ca l pho tographs sometimes aids th ei n t e rp re t e r b y prov id ing d imens ion a l rep re sen ta t ions o f

l a n d f o r m s or other objects of in terest . Al thoughs h a d o w s can affect th e pho to in t e rp re t e r 's dep th pe rcep -

tion, they are of ten an in valu able aid in est imat ingheights or dep ths of objects . In near ly flat t e r r a in , sub t l evar i a t i ons on the su r face which woul d o the rwi se bed i f f i c u l t to detect a r e e m p h a s i z e d b y s h a d o w s .

However , because objects in the shaded area reflect sol i t t le l ight to the spacecraf t camera, they are rare ly visi -

ble in space p h o t o g r a p h s .Tone and color percept ion are i m p o r t a n t elements in

th e analysis of pho tographs . O n b l ack -and -whi t e pho to -

graphs, dist inct ions be tween objects are observed onlyin t ones o f g ray . On co l o r pho tograp hs , hue b r igh tnessand s atu rat io n as wel l as tone can be used to dist inguishobjects. The color of surface objects , pa r t i cu l a r ly w h e nv iewed f rom space , r a re l y co r re sponds to t he g round-level percept ions. A body of water may appear in tonesranging f rom w hi t e to g reen to b l ack , depe nd ing on t heS un angle, th e v iewing ang l e , and the cond i t i on of thesurface ref lect ing l ight to the camera lens. A blackasp h a l t road may appear very l ight in tone because of i tssmooth su r face . W hen th e p h o t o i n t e r p r e t e r u n d e r -stands th e factors that govern th e p h o t o g r a p h i c to n e orcolor of objects of in terest , these charac t e r i s t i c s become

m a j o r clues to the i r i den t i ty or compos i t i on .

Texture in photographs i s the resul t of tonal repet i -t ions in groups of objects to o smal l to be discerned asin d iv id u a l objects. Thus, the size of an object requiredto produce t ex tu re var i e s wi th th e scale of the pho to -graph. In large-scale (1:5000) photographs, t rees can be

seen as i nd iv id ua l ob jec ts and the i r leaves or needles,

a l t hough no t seen separa t e l y , con t r ibu t e to the t ex tu reof the t ree crowns. Simi l a r ly , in small-scale (1:250 000)p h o t o g r a p h s , th e ind iv idua l tree c rowns , a l t hough n o tseen separa t e l y , m ay c o n t r i b u t e to the t ex tu re of thewhol e s t and o f trees. Thus, the tex ture of a grou p of ob-jects (e.g., a t imber stand of a cer tain species composi -

t ion) m a y b e dist inct ive enough to serve as a re l iableclue to the ide nt i ty of the objects .

Scient ists hav e stressed th e p a t t e r n , or the s p a t i a l ar-r angement and associat ion, of objects as an i m p o r t a n tc lue to the i r or igin , to t he i r func t ion , or to bo th .Geographers and an th ropo l og i s t s s tudy se t t l ement pa t -

te rns and t he i r d i s t r i bu t ion to u n d e r s t a n d th e effects ofdiffus ion and migra t ion in cu l tu ra l h i s to ry . Ou tc rop p a t -te rns pro vide geologists c lues to geological s t ru ctur e ,and drainage pat terns have order ly associat ion wi thst ructure , l i thology, and soi l texture . Th e vary ing re la -t ionships be tween vegetat ive elements and t he i r en -v i ronment p roduce some charac t e r i s t i c pa t t e rns ofplant associat ion.

M a n y regional pat terns and associations that for-mer l y could be studied only t h rough l abor ious g roundobse rva t ion are c l ear l y and q u ick ly visib le in space

pho tographs . Moreove r , these p h o t o g r a p h s m ay cap-tu re many s ign i f i can t pa t t e rns , such as fracture t races

and tonal "anomalies" t ha t th e ground observer mightover look or misinterpre t because of his l imi ted f ie ld ofv iew. Th e t rained observer appreciates th e signif icanceof space pho tograph s chief ly t h rough h i s unde r s t and ingof pat terns and associations on the Ear th su r face .

P R I N C I P L E S O F P H O T O G R A P H I C A N D D I G I T A L D A T A A N A L Y S I S 37 9



INTE RPRE TATIVE AC TIVITIE S

The interpreter observes ch aracter is t ics of the photo-gr a ph or image and determines the identi ty and signifi-

cance of the objects they represent . The analysis proc-ess occurs in a time sequence be gin nin g w ith a search

process that results in the detection of i m p o r t a n tfeatures , s o me of which may require measurement.Me asurement is fol lowed by considerat ion of thefeatures in terms of col lateral informa tion, usual ly non-p i c t o r i a l , f r o m t h e i n t e r p r e t e r ' s s p ec i a l f ie ld o fknowledge. On the basis of these ac t ions, hypothesesconcerning the identi ty and signif icance of the featuresare formed. Final ly , the interpreter must evaluate theident i ty and significance. In some instances, i t may bepossible to perform f ield checks to val idate his deduc-tions as to the identity of an object. Thus, the five im-por tant sequential ac t ivi t ies of pho to in terp re ta t ion in -clude search techniques, the use of indicators , measure-

men t , deductive reasoning, and f ie ld checking.Interpretat ion begins with c lose examination of al l

detai ls that a re considered relevant. However, most ex -per ienced interpreters prefer to begin by scanning thephotograph or image as a whole. I t is usually necessaryto study th e pho tograph or image with reference to anindex map or a photomosaic which serves as an indexmap. A large-scale map, preferably topographic, isuseful as a base map.

M a n y character is t ics m ay provide indications as tothe identi ty of an unknown object . No single indicatoris likely to be infal l ible; but if all or most of the indica-tors lead to the same conclusion, th e conclusion is prob-

ably correct. Photointerpretat ion, therefore, is h igh lydependen t on the science of probabil i t ies . Th e pr inc ip leinvo lved , known as "convergence of evidence," re -quires that the interpreter first recognize basic features

or types of features and then consider their arrange-m en t ( p a t t e r n ) in the areal conte xt . Several al ternativein te rpre ta t ions may be possible. W ith the a id of photo-in terpre tat ive keys , cri t ica l ex a m i n a t i o n of the evidenceusually reveals that al l interpretat ions except one areunlikely or impossible.

Photointerpreters can measure the exact dimensionso f features using scales an d o t h e r i n s t r u m en t s .Genera l ly , however , pho to in terp re ta t ive measurementinvolves ma king visual est imates of the s ize and shapeof an object. A reasonably correct estimate of d imen-sions is essential to correct ident i f icat ion. Plott ing anddrawing to known scales m ay also be regarded asfur ther activi t ies of measurement .

By means of deductive reasoning based on the pre-viously described activities, th e in terp re ter can identify

objects and features on the ph otograp h or image. On thebasis of these deductions, th e interpreter documents h isresponse by label ing (naming or descr ib ing) th e iden-

tif ied features. The labeled products are often calledthematic or classif icat ion maps.

M u c h scientific knowledge has been tested by the pa-t ient correlat ion of photographed or imaged featureswith ground features by means of careful field checking.M a n y established c orrelatio ns are taugh t as basic prin ci-ples in the var ious photointerpretat ion disc ipl ines.Nevertheless, in almost every inte rpr eta tive task,u n k n o w n s or uncer tain conclusions will ar ise that mustbe checked in the field. Th e interpreter should conductfield checking whenever feasib le to val idate his work.Some types of work require field correlation before andafter th e in terp re ta t ion . The amount of fieldwork

necessary varies with the requirements for accuracy,th e complexi ty of the area, th e quali ty of the photo-graphs or images, and the ability of the interpreter .

Digital Analysis Techniques

R O G E R M . H o F F E Rb

A N D A . V I C T O R M A Z A D F

Current procedures fo r processing and analyzingdigital data f rom the EREP Multispectral Scanner

b P u r d u e U n i v e r s i t y .cLockheed Elect ronics Company, Inc .

(S192) or similar systems involve four pr imary ac-t iv i t i e s : p r ep r o c es s i n g , d i s p l a y a n d en h a n c em en t ,analysis and c lassif icat ion, and evaluation. Althoughman y va r iat ions and com binatio ns of these ac t ivi t iesp rov ide a flexible analytical system, this section is in-tended to give a very brief overview of techniques usedby many investigators.

3 8 0 S K Y L A B E R E P I N V E S T I GA T I O N S S U M M A R Y



P R E P R O C E S S I N G D I SP L A Y A N D E N H A N C E M E N T

Preprocessing invo l ves var ious man ipu l a t io ns t ha tmake the data more usable . I t i s important to note thatno ac tua l da t a ana l ys i s o r i n t e rp re t a t i on occurs i n t h i sphase of the a c t iv i ty . A ma jor p reprocess ing ac t iv i t y

p e r f o r m e d on the digi tal data i s edi t ing, in w h i c h th eport ion o f the d ata of pa r t icu lar interest to inves t igator sis located and ext racted f rom the total data se t .O p t i c a l - m e c h a n i c a l systems record scanner data ine i ther a s t r a igh t or a con ica l scan - l i ne conf igura t ion .

L andsa t is typica l of the fo rmer , whe reas EREP (S192)is character ist ic of the lat te r . Because most users ofdigital data do not have the capabi l i ty to display con ica lscan-l ine formats, a special preprocessing of the S192data was r equ i red to d i sp l ay the da t a i n app rox ima te l ythe co r rec t geome t r i c ou tpu t fo rm at . Because geome t r i cdistor t ion across th e scene makes th e locat ion ofspecific geographic features diff icu l t , the conical scan-

l ine data were resampled and data tapes reconst ructedso t ha t th e data could be d i sp l ayed us ing s t r a igh t scan -l i ne d isp l ay equ ipm ent . This process enabled th e usersto d i sp l ay t he da t a wi th t he i r own equ ipment and stil l

ob ta in ou tpu t p roduc t s hav ing reasonab l y accura t egeometr ic f ide l i ty . Th e th i rd majo r t ask of preprocess-in g and reformat t ing involves digi tal f i l te r ing of theda t a t o im prove t he da t a q ua l i t y ( s igna l - to -no i se r a t i o ) .Pre l imin a ry w o r k w i t h th e SI92 da t a i nd i ca t ed t ha t

some wave l eng th bands we re ex t reme l y no i sy . These

noise p a t t e r n s w e r e c o m p l e x a n d i n c l u d e d b o t hsystemat ic and random noise . To decrease th e effect ofthe systemat ic noise, a series of digital noise filters w as

deve l oped , and m u c h of the SI92 da t a w as preprocessedw i th th e digital noise fi l ters.

For selected Earth resources studies, some invest iga-tors have subjected the i r data sets to a geometr ic correc-tion and ro t a t i on sequence designed to correct for theorbita l path of the sate l l i te and to enable display of thedata at a geom etr ical ly correct scale . Othe r inve st igatorshave pe r fo rmed add i t i ona l da t a p reprocess ing to ad jus tth e data values to a par t i cu l a r d i sc ip l ine r equ i rement ,in c lu d in g merging th e data fo r b a n d s w i th tw o scient if ic

data ou tpu t s , or have t r ansfo rmed th e data by mathe -mat i ca l methods in to an ent i re ly new se t of values. Afe w invest igators have registered the i r scanner data toother data sets, such as L andsa t -1 da t a or U.S. Geologi-cal Survey topograph i c maps .

The d i s p l a y of c o m p u t e r - e n h a n c e d d a t a c an assumeseveral forms. One of the more common procedure s isto i l l u m i n a t e i m a g e r y o f t h ree i n d iv id ua l wav e l eng thbands of the origina l sa te l l i te d a t a t h r o u g h a p p r o p r i a t e

color f i l te rs to obtain false -color composi tes . Usingdig i ta l data , channe l s can be assigned to the three colorguns of a catho de- ray dev ice and thus c reate a fal se -co l o r -compos i t e image . Th i s approach has been suc-cessfully used fo r t he L andsa t da t a . Numerous com-

b ina t ions of fal se -color-composi te images can be ob-t a ined .

A var i e ty o f mathem at i ca l func t ions can be app l i edto the digi ta l data to enhance d i sp l ay . The data va l uerange may be expanded or compressed to increase ordecrease contrast , or data value ranges m a y b e seg-mented wi th colors assigned to ident i fy d i f fe ren t

ranges. Data values m a y b e combined by add i t i on and

subtract ion or may be rat ioed to emphasize degrees ofs imilar i ty or d i f fe rence be tween channe l s . By t ak ingmathemat i ca l t r ansfo rms of g roups o f channe l s , en -tirely new da t a sets may be formed to isolate a pa r t icu -

la r feature in the data.

A N A L Y S I S A N D CLASSIFICATION

D u r i n g th e past decade , considerable progress h asbeen m a d e in the d e v e l o p m e n t of c o m p u t e r - a i d e danal ys i s t e chn iques i nvo l v ing t he ap p l i ca t ion o f pa t t e rn

recogni t ion theory to mul t i spec t r a l scanne r da t a . Th ebasic procedure used for analysis of mul t i spect ral scan-

ner data n orm al l y inc l udes th e fo l l owing steps.1. Defini t ion of the parameters of the c lassi f icat ion

prob l em2. Selection of a classification technique3 . Ident i f icat ion of areas wi th in th e scene fo r w h i c h

reference data ( i .e . , ground t ruth) are known4. Calculat ion of var ious stat i s t ical parameters for

th e area of in terest5. Classi f icat ion of the data into spect ral classes

6. Disp l ay and /o r t abu l a t ion of the classi f icat ion

results

The fi rs t step in classi f icat ion consists of the for-mulat ion of a se t of object ives against which the f inal

resul ts wil l be measured, the establ ishment of a pro-cedura l ana l ys i s p l an , and the selection of a data set .

P R I N C I P L E S O F P H O T O G R A P H I C A N D D I G I T A L D A T A A N A L Y S I S 3 8 1



The objectives m ay inc lude such i tems as the desi redaccuracy s t andards or i n f o r m a t i o n a l c o n t en t of the f inal

produc t . Th e procedura l p l an ou t l i ne s th e major s t eps

and cont ingencies to be fo l l owed and de f ines th eclass if icat ion algo ri thm to be used. A data se t th at i s ap-pro pria te for the object ives i s se lected. The se t may in-c lude a smal l a rea abou t which de t a i l ed i n fo rmat ion isdesi red, may be a test area f rom which inferences to amuch larger area are poss ib l e , o r may actua l ly i n c l u d e are l a t ive ly l arge geographic area ( i .e . , several thousandsquare hec tome te r s ) .

Sample areas for which de tai led reference data ( i .e . ,ground t ruth) a re avai lable are identified in the data setto develop a t ru ly r ep re sen ta t ive se t o f t r a in ingstat i s t ics . Reference data may also include resul ts offield su rveys o r r ad iom e t r i c measurement s made a t t het ime of data col lec t ion, as wel l as informat ion fromp h o t o g r a p h s and m a p s . Th e sampl e a reas are locatedw i t h i n the data set and labeled for fu tu re use. Some of

the sample areas are designated "t raining areas," and

th e ref lec tance values of these areas are used to de f ineth e classi f icat ion stat i s t ics . Other sample areas, desig-nated test areas, a re reserved fo r eva l ua t ing th e accuracyof the f inal p r o d u c t .

The two basic c lassi f icat ion techniques are super-vised an d unsupe rv i sed . In the supe rv i sed t e chn ique ,th e c o m p u t e r , in essence, compare s th e stat i s t icalparam e te r s o f e ach po in t ( p i c tu re e l ement o r p ix e l )

w i t h t he s t a t i s t i ca l parame te r s o f known su r facefeatures se lected b y the ana lyst . Based on proba b i l i ty

decisions def ined by the c lassi f icat ion algo ri thm used,th e computer assigns each data point to the most s imi -

la r defined feature type . This supervised c lassi f icat iont echn ique is used when th e features o f known in t e re s tare easily located in the data set and are homogeneousin character . For exampl e , when an ana l ys t knows t ha ta part icular agr icul tural crop w as imaged in a specif icpor t i on of the data, this area can be ident i f ied and usedas a " t r a in ing field" f rom which spec t ra l r e f l e c t ancevalues can be determined . Such t rainin g f ie lds aredefined fo r several crop species and cover types. Thedata values for each remaining data point in the scene

then a re compared to the ref lec tance values of the t rain-in g dat a and classi f ied, on the basis of the proba b i l i ty

param eters , in to one of the crop species or cove r- typ e

categories def ined by th e t r a in ing data . Af t e r classifica-

t i o n , t h e a n a l y s t m a y also assign a "threshold"

parame te r t ha t de f ine s th e m a x i m u m a m o u n t o f

difference acceptable be tween th e data po in t r e f l ec t ance

values and t he re f l e c tance va l ues of the k n o w n fea turet ype . If the p ro bab i l i t y decision falls below a de f inedthreshold level , the data are displayed as a b l a n k .

In th e unsupe rv i sed t e chn iqu e , o ft en ca l l ed "c lus t e r -ing," th e data points are classi f ied on the basis ofs im i l a r i t y to other data points in the scene . The com-p u t e r examines the spect ral s ignature of each data pointin the scene and then statistically divides the ent i rescene into th e n u m b e r of spectral classes or g roupsspecified by the ana l ys t . Th i s t e ch n ique is used whenfeatures of k n o w n i n t e re s t c a n n o t be specifically locatedin the scene or are not hom ogeneous. For exam ple , anan a lys t in terested in a w i ld - l a nd area con ta in ing a veryc o m p l e x m ixt u re o f cove r t ypes may p rogram the com-puter to classify th e scene into 12 or 16 groups hav ingsimi lar spect ral character ist ics . A fte r th e classi f icat ionhas been pe r fo rm ed , the a na l ys t a tt aches a s ignif icance

to the classes on the basis of some other reference infor -mat ion , such as an aeria l p h o t o g r a p h .

Some analysts use a c o m b i n a t i o n of the two tech-niques to t ake advan tage of the special features of each.Regardless of the tech niqu e , i t is impo rtant to recognizethat , in most cases, th e resul ts obtained are as m u c h afunct ion of the manner in which the analyst has inter -faced w i t h th e data as they are of the p a r t i c u l a ra lg o r i th m be ing used . A nal ys t sk i l l s in q ua n t i fy ing th e

o v era l l ob jec t ive s and in unde r s t and ing t he compute r -

processing system are of cr i t ical impor t ance in t heeffective use of computer-aided analysis techniques.

Classif icat ion of the data i s accompl ished by thec o m p u t e r , using one of several possib le algori thmsavai lable . The m axim um l ike l i hood based on Gaussi and is t r ibu t io n has been commonl y used in the past andwas the algo ri thm used in several of the Sky lab in-

vestigations. Other decision strategies can be used thatemp l oy func t ions based on l i near d i sc r im ina t ion o rgeome t r ic p r ox im i ty (neares t ne ighbor ) . The com pute rt ime required for the actual c lassi f icat ion task m ay

range from a few seconds to several minutes, depending




on the n u m b er of waveleng th bands in the data set, th enumber of spectral classes defined, the type of com-puter , and the efficiency of the software. It is also im -portant to recognize that the classification can be ex-tended to relatively large geographic areas. It is these

types of classification tasks, involving t housands ormil l ions of square hectometers , that most effectivelyuse the power of the computer (e.g., rapid classificationand tabu la t ion of large quantities of data) .

Disp l ay of the classification results is n o r m a l l y ac -complished by using ei ther an image- type or a tabularforma t . Image- type formats , of ten obtained f rom a stan-dard computer l ine p r in ter , p r in t out a symbol that isd i s t inc t ive for each classification category. The symbolsare arranged in the sequential fashion of the data andpresent a geographic d istrib utio n of the results. Directimage formats provide s imilar information but usecathode-ray tubes or film recorders to display theresults, often with colors to indicate th e various covertypes and to identify their location. This technique isuseful fo r compar ing th e results with maps or aerialphotographs.

Tabular formats may be summary statistics tha t indi-cate th e number of data points classified into eachcategory. These fo rmats ar e used when estimates of thetotal area of a class type ar e desired, such as the numberof square hectometers of hardwood forest in the scene.Because each data point or resolution element ofsatellite data represents an area on the ground (approx-imately 0.56 hmVresolution element for the reformat-te d S192 data), a conversion factor is appl ied to deter-mine th e number of square hectometers in each cover

type of interest. The percentage of the entire classifiedarea, as well as the area covered by each of the speciesor cover types of interest, can be rapidly calculated.

ANALYSIS EVALUATION

Anal y t i ca l results are evaluated using both qualita-t ive and quanti tat ive techniques. The analyst may ob-tain a quick subjective impression by compar ing th e dis-play of the classification results with an aerial photo-

graph or a thematic map. When sat isf ied that th e prod-uct is general ly acceptable, he then under takes a moreobjective evaluat ion. Quantitative evaluation is ex-

t remely important for assessing the accuracy of theclassification obtained at different times of the year or

for com par in g resul ts obtained f rom the use of dif ferentcombinations of wavelength bands in the analysis.In th e mo s t co mmo n ap pro ach , test areas reserved

dur ing th e p r e l i m i n a r y analyt ical stages are evaluatedby compar ing the known reference information withthe classification results. Any data point classified intoth e same category as defined by the reference informa-t ion is called "correct"; others ar e errors. Standardstatistical techniques ar e then used to determine th equant i t a t ive accuracy and significance based on thenumber of correct and erroneous data points in the testarea. Depending on the n u m b er and adequacy of thetest areas, th e tested accuracy can be projected to the en-tire scene.

Another test can be per fo rmed by compar ing th etotal area classified in a category with the total areaderived from s o me other source, such as census- typedata or areas obtained by interp retation of aerial photo-graph s. Classification errors for ind ivid ual data po intsm ay be averaged over th e entire scene. Fo r example, ifth e n u m b er of "forest" data points misclassified as"o t he r" is equal to the number of "other" data pointsmisclassified as "forest ," th e total area of the forest m aybe correc t even though nume rous in divid ual data pointsmay be misclassified.

M a n y researchers believe that th e major potential ad -vantage of digital processing is the quanti tat ive nature

of th e available information. Preprocessing activitiesfacil i tate accurate formatt ing of the geometric andradiometr ic qual i ty of the data to fit the user's specificrequirements . Display an d en h a n cemen t techniquescan be used to emphasize features of par t icular interest.Analysis an d classification can be accomplished in aconsistently accurate and systematic manner. Statisticalevaluation steps indicate the degree of classification ac-curacy with in a scene and among dif ferent scenes. W i t hthese tools, th e computer-assisted analyst can makescientifically valid, objective decisions concerning th eEarth's resources.

P R I N C I P L E S O F P H O T O G R A P H I C A N D D I G I T A L D A T A A N A L Y S I S 3 8 3






A P P E N D I X E

Standard W eather Symbols

A, B

W i nd D i rect ion an d W i n dspeed

S y m b o l

©

»—

N

\ > —

*

^

^

X^s

\£!> —

\\\v

k

*»—

L

k l>

—_

kk_

S p e e d ,k n o t s

C a l m

3 - 7

8 -12

13 -1 7

1 8 - 2 2

2 3 - 2 7

28 -32

33 -37

38 -42

43 -47

48 -52

53 -57

58 -62

63 -67

68 -72

73 -7 7

103 - 107

Speed,

m / s e c

C a l m

1 .5 - 3 . 6

4. 1 - 6. 2

6. 7 - 8. 7

9 . 3 - 1 1 . 3

1 1 . 8 - 1 3 . 9

1 4 . 4 - 1 6 . 5

1 7 -1 9

1 9 . 5 - 2 1 . 6

22.1 -24.2

24. 7 - 26. 7

27. 3 - 29. 3

2 9 . 8 - 3 1 . 9

3 2 . 4 - 3 4 . 5

35 -3 7

3 7 . 6 - 3 9 . 6

53 -5 5

G F C } I

H

A D irection from w hich wind is blowing (See symb ols at left.I

B W indspeed (See symbols at lef t . )

C Ex ten t of cloud cover (See symbols be low. I

D Barometr ic pressure reduced to sea level, ki lopascals (mil l ibars)

E A ir temperature at t ime of report ing, kelvin

F W e a t h er condition at time of repor t ing (See symbols below.)

G Vis ib i l i t y , meters

H De wpoint tempe rature, kelvin

I Pressure change during th e 3-hr period preceding observ ation,

k i lopasca ls (mi l l i bars)

J Hei gh t of base of lowest cloud, meters

M i s s in g o r unavai lab le data ar e indicated by "M" in the proper location.

Cloud Cover P resent W eather Cond i t ions

Symbol

O

o(3(B39«

O•

P ercent covered

Clear

Up to 10

20 to 30

40

50

60

70 to 80

90 or overcast

wi th open ingsCompletely

overcast

Sk y obscured

Symbol

fW

oo

»

• •

•• •

*

•

V#

V

Exp la na t ion

Vis ib i l i ty reduced

by smoke

Haze

Intermittent drizzle (not

f r eez i n g ) , slight

Continuous rain (not

f reez ing) , slight

Cont inuous rain (not

f r e e z ing ) , moderate

Intermittent snow,

sl i gh t

Sl i gh t rain showers

Sl i gh t snow showers

(wind direction)

385



Temperature P ressure

Kelv in

30 5 —

3 00 —

295

2 90 —

2 85 —

2 8 0 —

2 75 —

2 7 0 -

2 65 —

2 6 0 —

2 55 —

2 5 0 -

2 4 0 —

Fahrenhe i t Kilopascals

im° me c

— 90°

-80°

— 70C 103

'5

— 60°in? 5

— 50°102

-40°

3fl° inn c•^ 1UU. ?

-20°

— 10C

O R S— 0°

10°VO

—20°

96.5

—30'

M i l libars In

1UI?

imn

1UUU

OO R

oon

QAE

oan

Q7C

o?n

— 965

(32° F )

30.5

V

29.5

28.5

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