Lecture Outline Analysislearnline.cdu.edu.au/units/ses201/lectures/ENV202_L4.pdf1 ENV202/502 –...

1

ENV202/502 – Introductory Remote Sensing Wk 4

Dr Karen Joyce

School of Environmental and Life Sciences

Bldg Purple 12.3.091

Lecture 4 – Aerial Photography and Image

Analysis


Lecture Outline

• Revision

• Aerial photography history

• Camera types

• Image acquisition and distortion

• Annotation elements

• Photography basics – focus, exposure, aperture

• Making measurements – scale, distance, area, relief displacement

• Interpretation cues and keys

• Applications

• Field trip


What Controls EMR Interactions within

Vegetation?• Within leaf

– Photosynthetic processes,

– Photosynthetic + non-photosynthetic pigments,

– Water content, – Self-defense/regulatory

mechanisms,

– Leaf internal and external structures

• Leaf

– Internal

(structure, chemistry, processes)

– Form/morphology

– Orientation

– Coating

• Canopy

– Density and arrangement

of leaves

– Crown form and layering

• Stand

– Structural properties

– Topography/microclimate

– Biomass

• Community



Water?

• Water-interactions:

– Air-Water interface + atmosphere

– Water column

– Substrate features

(sediment, benthic flora and fauna)

• Water-column:

– Absorption and Scattering

– Suspended and Dissolved matter

• Key controls:

– Surface roughness

– Organic matter

– Inorganic Matter

– Depth

– Substrate type

Source: S.Phinn



Minerals and Soils?

• Minerals

– Similar controls on interactions as atmospheric gases

– Atomic level interactions of light with different minerals is unique due to their structure

– Results in distinctive mineral absorption spectra

– Source of minerals data: http://minerals.gps.caltech.edu/

• Soils

– Main controls:

- Mineral content (e.g. iron oxide)

- Organic content (e.g. leaf litter)

- Roughness / texture (sand, silt, clay)

- Moisture content

Source: S.Phinn ENV202/502 – Introductory Remote Sensing Wk 46

Imaging Sensor Dimensions

• What controls the type of information you can extract from an image or a photograph taken from an aircraft or satellite ?

Source: S.Phinn

Image Information Controlling Dimension

Size of objects and features Spatial

Colour of objects and features Spectral

Contrast between objects and features

Radiometric

Time of day, year, tidal cycle, growth cycle

Temporal

2


Resources

• Thomas M. Lillesand, Ralph W. Kiefer, Jonathan W. Chipman (2008) Remote Sensing and Image Interpretation, 6th Edition. John Wiley & Sons, Hoboken, NJ. ISBN 9780470052457. Chapters 2,3,4

• Northern Territory Library Aerial Photo collection http://www.ntl.nt.gov.au/collections/aerial

• NASA Remote Sensing Tutorial - Aerial Photography Section http://rst.gsfc.nasa.gov/Sect10/Sect10_2.html

• Australian Spatial Data Directory http://asdd.ga.gov.au/

• Australia's largest aerial survey company - Fugro Spatial Solutions Pty Ltd. http://www.fugrospatial.com.au/

• RSCAL module 3 – Aerial Photo Interpretation


Aerial Photographs

• Original remote sensing data source

• Historic development of remote sensing

• Current status of this technology

• Future of aerial photography

• Digital camera systems

– matching spatial resolution– multi-spectral

– digital, georeferenced data

– temporally stable– automatic terrain correction

– generation of elevation surfaces and orthophotos

Sourc

e: IS

PR

S H

ighlig

hts

2004

Source: S.Phinn


Sem.1. 2009- Lecture 4 GEOM2000/7000 Remote Sensing of Environment

Filmprocessingin darkroom

FCIR

Color

B&W

Stereo plotter

Films used alternatively

RGB & NIR

GIS

DTM

Orthophotos

Mapping

Revision

Visualization

Image analysis

ClassificationDigitalwork-station

Post Processing Software

Analogue workflow

Digital workflow

PrinterColor MSB&W

Archivesystem

Color FCIRB&W

Photoscan

Film

Data storage

Film vs. Digital Workflows

Source: G.Kelly ENV202/502 – Introductory Remote Sensing Wk 410

Source: G.Kelly

DMC Panchromatic Image


Source: G.Kelly

DMC True Colour Image


Source: G.Kelly

DMC Colour Infrared Image

3


Current Airborne Systems

LINE-ARRAYS Size Bands

Leica ADS-40 12,000 wide 4 pan, 8 MS

DLR HRSC 12,000 wide 5 pan, 4 MS

Jenna Optronik 12,000 wide 5 pan, 4 MS

FRAME ARRAYS

Integraph DMC 13,824 x 7,680 4 pan, 4 MS

MS Vexcel Ultracam 14,430 x 9,420 9 pan, 4 MS

DiMac 10,500 x 7200 4 pan


Camera Types

• Vertical frame (metric or mapping)

• Large format camera

• Strip camera

• Multi-spectral or multi-band camera

• Panoramic camera

• Oblique cameras (high and low)

Source: S.Phinn


Vertical Aerial Photos





• Geometric distortions due to aircraft motion

– Roll

– Pitch

– Yaw

Source: Biology-resources.com / NASA ENV202/502 – Introductory Remote Sensing Wk 418

Geometric Distortions

4


Radiometric Distortions

• Radiometric distortions due to viewing angle differences in overlap areas


Photographic Elements

• Annotation

– Date

– Level

– Run number

– Frame ID / Photo number

– North point

– Exposure

– Flight heading

– Flying height (AGL = above ground level or terrain (H’), ASL = above datum or sea level (H))

– Focal length

– Copyright

• Fiducial marks (corners, sides)

– Use to locate photo centre

• Principal point

– Exact centre of photographic frame + Basis for measurements

• Conjugate principal point

– Principal points in overlapping photos

• NADIR point

– Ground point directly below camera optical axis.

Source: S.Phinn


1:25000 Colour aerial photograph,

Amity Point, North Stradbroke Is. Copyright: Queensland

Dept. of Natural Resources

Source: S.Phinn

Photographic Annotation Elements


Geometry

Heights

H = height above datum (from altimeter)

H’ = height above terrain

h = terrain elevation above datum

H’ = H – h

Source: S.Phinn


• A ratio of distance (d) on an aerial photograph to the same distance on the ground (D).– S = aerial photo distance/ground distance = d/D

• Scale calculation over flat terrain:– S = d/D or

– S = f/H’ = f / (H-h), where f = focal length and H’ = height above terrain

• For variable terrain H’ will change over the photographed area, use an average H’

• Express scale in specific units as:– Representative fraction 1 / 25,000

– Ratio 1 : 25,000

– Verbal – 1cm on the photo = 250m on the ground

Scale

Source: S.PhinnENV202/502 – Introductory Remote Sensing Wk 4

24

Scale Calculation

• Eg. Distance on photo (d) –measure with a ruler = 2cm

• Distance on ground = 500m

• Ensure units are the same

• 2cm = .02m

• S = 0.02 / 500

• Divide top and bottom by the numerator

• If you get an answer like 0.00004, this is incorrect…

• S = 1 / 25000

• Or, 1cm on the photo = 250m on the ground

S = d/D

Where, d = distance on photo

D = distance on ground

5


Scale Calculation

S = f/H’

= f / (H-h)

Where, f = focal length

H’ = ht above terrain

• Eg. focal length (f) = 152mm

• Flying height (H)= 5,000m ASL

• Average terrain (h)= 100m

• Height above terrain (H’) = 5,000-100 = 4,900m

• Ensure units are the same –152mm = 0.152m

• S = f/H’

• S = 0.152/4,900

• Divide top and bottom by the

numerator

• S = 1 / 32237

• Or, 1cm on the photo = 322m on the ground


Large Scale or Small Scale?

• Scale is a fraction eg 1 / 25,000

• Therefore ‘large’ or ‘small’ refers to the size of the fraction

• A low detail, large area map may be 1 / 250,000

• A high detail, small area map may be 1 / 5,000

Small!

Large!


Distance and Area

• Distance calculation over flat terrain

– Calculate scale of photograph

– Measure distance on photograph

– Convert distance to scale units

– Multiply scale denominator by distance


Relief Displacement

• The radial distance between an object’s image and its true plan position which is caused by changes in terrain elevation or object height.

• Top of the feature lies further from the photo center than the base

• Vertical feature appear to lean away from photo center


Relief Displacement


Relief Displacement

• d = rh/H’

• d = relief displacement

• r = radial distance on the

photo from the principal point to the top of the displaced feature

• h = Height above ground of

the feature

• H’ = Flying height above the

ground

d will increase if r and/or h increase

d will decrease if H’ increases

6


Relief Displacement

• d = rh/H’

• d = 2.01mm

• r = 56.43mm

• Flying height above ground H’ = 1220m

• Rearrange equation: h = dH/r

• h = 2.01 x 1220 / 56.43

• h = 43.4m

PP

What is the height of the tower?


Image Interpretation

• Systematic approach from general to specific interpretation

• Interpretation involves both:

– Detection of a feature

– Identification of a feature

• Automated photo and image interpretation now uses this technique

Source: S.Phinn


Aerial Photography Analysis Success

• Perceptual ability

• Training

• Experience

• Discipline knowledge (forestry, geology, soils etc)

• Equipment (stereoscope, magnifying scale etc)

• Ancillary data (maps, fieldwork, reports etc)


Interpretation CuesCue Terminology Example

Tone /

Colour

Dark, light, bright,

dull

Dark Blue (water)

Texture Smooth, rough Rough (urban area); Smooth (grass) –

function of scale

Shape Rectangular,

eliptical, regular,

irregular

Rectangular (crops)

Size Relative or

absolute

Small / large or 200x100m

Pattern Regular, random,

gridlike

Repeating linear rows (vineyard)

Shadow Presence,

absence

Long shadows observed to the SW of the

feature (can indicate height of object, time of

day, southern hemisphere). Influences tone

and texture

Site /

Association

Description of

spatial

relationships

Large carpark beside large building (may

indicate shopping centre rather than factory)


Dichotomous Keys


Minimum Mapping Units

• Smallest size entity to be mapped as a discrete feature

• Small MMU = high detail

• Large MMU = low detail

• Small MMU can be a step in the hierarchy of a large

MMU – e.g. river, lake, stream, creek, can be grouped together to the larger MMU of water body

7


Classification Guidelines (from USGS LU/LC

mapping)

• Overall accuracy <= 85%

• Individual category accuracy should be about equal

• Repeatable results between interpreter and over time

• Applicable over extensive areas

• Suitable for use with data obtained at different times of the year

• Categories should be divisible into more detailed sub categories

• Aggregation of categories must be possible

• Comparison with future date should be possible

• Multiple uses of a category should be recognised where possible


Interpretation and Class Aggregation


Image Interpretation

• What features can you see in this image

and what interpretation cues

would you use to create a key for different features?


Classification Example

40

Worldview 2 Image

Non Water Water

LandInter-tidal

Trees Grasses Artificial Surfaces

Housing Commercial /

Industrial

Roads Jetty WaterInter-tidal Trees Grasses

Dark or bright?

Small, urban pattern

Assoc. trees,

grass

Not greenGreenCircular, rough,

shadows

Irregular shape, smooth

Large, Assoc. main roads

Long, thin

Surrounded by water

Btn land and water


Aerial Photography and Geology


Infrastructure Mapping

Source: AAM

8


High Resolution 3D Mapping / Modelling

Source: AAM ENV202/502 – Introductory Remote Sensing Wk 444

Mine Site Monitoring

Source: Fugrospatial


Landcover / Landuse

Source: Fugrospatial ENV202/502 – Introductory Remote Sensing Wk 446

Geothermal Assessments


Low Cost Aerial Photography

S.Bayley, Horizons Regional CouncilENV202/502 – Introductory Remote Sensing Wk 4

48

S.Bayley, Horizons Regional Council

Low Cost Aerial Survey

9


NASA Ikhana Unmanned Airborne System

• To Support Airborne Wildfire Monitoring Capabilities, a Number of Key Variables Were Identified:

• Ability for long endurance / long legs.

• Linger ability

• Medium to High Altitude

• Autonomous Payload Capability

• Operate in Hazardous Conditions (if necessary)

Ikhana capable of ~24-hour mission endurance; ~4000 miles; >40K feet altitude; Payload to 1500 lbs

Ikhana is Native American-Choctaw word meaning: “intelligent, aware”

V.Ambrosia et al., NASA ENV202/502 – Introductory Remote Sensing Wk 450

Data Collection and Distribution

Payload GCS

FTP Server

FTP mirror site

Data Processing•KML conversion

•WMS•CAP notification

Publishweb server

ArcGIS @ IC

•GEOTIFF

•Shapefile

Google Earth

WMSInternet

V.Ambrosia et al., NASA

• Primary products: GEOTIFF and Shapefiles• Data usually available within 3-5 minutes

• Google Earth and WMS provide first look at data• Message notifies when data are available


UAV Process


Grass Valley Grass Valley Grass Valley Grass Valley

& Slide Fire & Slide Fire & Slide Fire & Slide Fire

October 24October 24October 24October 24

UAV Imagery in Google Earth


V.Ambrosia et al., NASA

The UAV in Perspective


Global Hawk

10


Field Trip

• This Thursday 28th March

• Bus departs 8.15am outside CDU bus stop

• Noonamah pick up 9am, Bachelor at 9.40am

for those students who have already requested

it

• Make sure you wear:

– Comfortable, CLOSED shoes (not thongs or

sandals)

– Appropriate clothing, including long pants

55ENV202/502 – Introductory Remote Sensing Wk 4

Field Trip

• Make sure you bring:

– Clip-board with paper or exercise book

– Pens/pencils

– Ruler

– Scientific calculator

– Food and drinks for the day (NB: there will not be any

opportunity to purchase food or drink during the day)

– Sunscreen

– Aerogard or similar

– Hat

– Togs / towel if you plan to swim at lunch

– Change of clothes / shoes if the weather is wet

56


Coming Up

• 1st Practical assessment due – Image Characteristics and Dimensions

• Easter Break next week (no lecture or prac)

• Next lecture – Digital Image Processing - 1

• Next prac – Digital Image Processing part 1

Date post:	19-Sep-2020
Category:	Documents
Upload:	others
View:	0 times
Download:	0 times

Lecture Outline Analysislearnline.cdu.edu.au/units/ses201/lectures/ENV202_L4.pdf1 ENV202/502 –...

Documents