16 e Symposium canadien sur /a teledetectionth Canadian Symposium on Remote Sensing

8e Cohgres de L'Association guébecoise de teledetection0 1993 L'AQT/CRSS

THE OREGON TRANSECT ECOSYSTEM RESEARCH (OTTER) PROJECT

R.H. WaringCollege of Forestry, Oregon State University

Corvallis, OR 97331 U.S.A.E-mail: dwaring @ Lternet.edu ; FAX (503)-737-2668

ABSTRACT

The project compared the rates of carbon, water, and nitrogen movement through a rangeof Pacific Northwest ecosystems against those rates predicted by a simulation model.Remote sensing techniques were employed to extend the model's application.The project'sorganization and collaborative nature played an important role in achieving its objectives.

RESUMELe projet consistait a comparer les taux de mouvement du carbone, de l'eau et de l'azote[ravers une variete d'ecosystemes de la region du Nord-Ouest de la cote du Pacifique parrapport aux taux derives de l'utilisation d'un modele de simulation. Les techniques deteledetection ont ete utilisees pour etendre les possibilites d'application du modele. Le typed'organisation du projet et l'esprit de collaboration qui l'a mime ont joue un role essentieldans l'atteinte des objectify.

INTRODUCTION

The OTTER project was designed to test the generality of an ecosystem simulation modelacross a transect in Oregon at 44 0 N Latitude. The ecosystem model was developed byRunning and Coughlan (1988) and modified by Running and Gower (1991). The transectencompassed rain forests, subalpine forests, and arid juniper woodlands--reflecting nearlythe full range of forest productivity found in North America. Six sites along the transectwere selected for intensive ground and airborne analysis. At three of the sites the effects ofnitrogen enrichment upon ecosystem processes were observed in comparative studies withadjacent, unenriched systems. The ecosystem model was initialized by ground surveys ofthe vegetation and soil. The model was driven at a daily resolution with meteorologicaldata As a specific objective of the OTTER project, we sought remotely sensed surrogatesfor the conventional ground measurements to allow application of the model across theentire region. The success of the project rested on how well we could coordinate field andremote sensing measurements and from these comparative data, distill biospheric principlesthat would scale.

ORGANIZATION

A core group, all of whom had worked previously along the transect in Oregon, designedthe OITER project. The major facets of the project included: (1) ground measurements, (2)remote sensing from aircraft and satellites, (3) simulation modeling, and (4) an interactivecentral data system. The people responsible for these four areas communicated regularlythrough electronic mail to adjust schedules and set priorities.

Co-project leader, David Peterson at NASA's Ames Research Center, had responsibilityfor coordinating all remotely sensed studies. I took responsibility for all fieldmeasurements. There were two data banks, one at NASA Ames under direction of GaryAngelici for storing digital images, the other at Oregon State University under direction ofSusan Stafford for handling the field data. These data systems were linked to one anotherand to each investigator. Most of the ecosystem modeling was done by Steve Running andhis colleagues at the University of Montana. Instrument calibration was done at NASAfacilities at Ames, the Jet Propulsion Laboratory, Goddard Space Flight Center and at YorkUniversity in Toronto, Canada. Scientists from these institutions also collaborated in theproject. Additional scientists collaborated in the project from the University of California atDavis, the University of Idaho, Boston University, the University of Colorado, the

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University of Minnesota, and the Forest and Range Experiment Station in Fort Collins,Colorado.

Because ecosystem processes such as photosynthesis, transpiration, and decompositioncontinue all year in some parts of the transect, we required that remotely sensed data andsupporting ground measurements be collected each season. Coordination was facilitated byhaving NASA, the main sponsor of the research, designate the project as a Multi-sensorAircraft Campaign. With this designation we were able to guarantee flights with a variety ofsensors on three NASA planes ( ER-2, C-130, DC-8 ) and on an ultralight aircraftbelonging to Oregon State University. Once dates for the seasonal coverage by NASAaircraft were set, we invited other groups to compare additional sensors on the ground,from booms, and from a variety of other aircraft and satellites. At the times of scheduledoverflights , we also provided information on atmospheric properties using ground-basedsunphotometers.

Although all investigators met only a few times during the 3-year project, coordination wasnot a problem. We set policies for exchanging data through the data banks. We alsoestablished authorship and priorities on papers so that data could be assembled to meetschedules. The scientists in Oregon had two decades of experience to draw upon and anestablished data bank (Waring and Franklin, 1979). The ecosystem model was wellprescribed, defining exactly those variables that must be measured and others that couldserve as cross-checks on predicted fluxes. Electronic mail provided a means of keepingpriorities clear and altering schedules when necessary. Everyone involved was an expert intheir field, permitting us to focus on integration rather than technique development for themost part. The four field campaigns brought collaborators into close contact with the coregroup for extended periods. Good rapport. among investigators, a well defined model, andan interactive data system helped in setting priorities and in analyzing data sets in a logicalorder.

SCALING FROM FIELD SITES TO SATELLITES

The most important structural variable in the terrestrial ecosystem model was the leaf-area-index (LAI) of the vegetation (Running and Coughlan, 1988). From the ground, we usedthree independent methods to assess this variable (Runyon et al., 1993). With confidencein these estimates we then employed four airborne sensors (TMS, AVIRIS, CASI, andSE590) to determine spectral reflectance in the near-infrared and red bands. Whenappropriate atmospheric corrections were made, each of these remote sensing systemspredicted measured LAI with r2s above 0.9, sufficient to discriminate the < 30% annualvariation in canopy leaf area observed in the evergreen forests of the region (Spanner et al.,1993). In scaling to satellites we extended the grid size from less than 30 m to 1.1 km(AVHRR). In the winter season, rapidly changing atmospheric conditions combined withlow sun angle to cause overestimation of LAI on some sites (Goward et al., 1993). Byhaving a variety of independent ground and airborne systems of measurement, we wereable to cross-check nearly all estimates and identify when instruments went out ofcalibration or measurements proved otherwise unreliable.

Another important structural variable, particularly in forest ecosystems, is the carbon storedin the standing biomass (50% of dry weight) of tree stems and branches. Because the01-1ER project covered a range of standing biomass from 10 Mg/ha to over 700 Mg/ha, itoffered an excellent test of various sensors. Synthetic aperture radar (SAR) was useful upto about 150 Mg/ha but not above ( Moghaddam et al., 1993). Multispectral satellite datafrom the Landsat Thematic Mapper with 30 m spatial resolution was used at different viewangles and seasons to distinguish various structural properties of vegetation, includingstanding biomass up to levels of about 500 Mg/ha but with less accuracy than SAR withinits range of sensitivity (Wu and Strahler, 1993). Cohen and Spies (1991) using red, nearinfrared, and mid-infrared bands in TM had good success in classifying various age classes

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of young, mature, and old-growth forests in the Pacific Northwest. The reliability of thisapproach, however, has not been critically tested on forests with standing biomassapproaching maximum values above 1000 Mg/ha for Douglas-fir and up to 2500 Mg/hafor coastal redwood (Waring and Franklin, 1979).

Photosynthesis is the process which converts CO2 in the atmosphere into carbohydrates tobuild and sustain plant life. The upper limits on photosynthesis are set by the amount ofincoming solar radiation (400-700 nm) intercepted by the vegetation. The Total OzoneMapping Spectrometer (TOMS) has been shown to estimate accurately the integratedmonthly radiation from daily passes over a 2.5 x 2.5 0 field of view (Eck and Dye, 1991),even in the mountainous topography of Oregon (Goward et al., 1993). The fraction ofradiation that can be absorbed by vegetation is closely related to monthly assessments of theNormalized Difference Vegetation Index (NDVI).

The rates of most ecosystem processes are strongly affected by temperature. We firstconfirmed from thermal sensors on board the ultralight aircraft that the canopy temperatureof dense coniferous forests was always within 2°C of ambient air temperatures (McCreightet al., 1993). We then showed that ambient air temperature could be estimated from theultralight aircraft in less dense vegetation by extrapolating the surface temperature/NDVIcurve to the equivalent of dense forest cover (an NDVI value of 0.9). When this approachwas extended to satellite AVHRR coverage on a 9 X 9 km scale it proved capable ofestimating ambient air temperatures within 3°C across the transect, except when snow waspresent (Goward et al., 1993).

Soil drought is another environmental variable that places important constraints on mostecosystem processes. As the surface litter and soil thy, the slope of the relationshipbetween surface temperature and NDVI becomes steeper as demonstrated on repeatedultralight flights (McCreight et al., 1993). The steeper the Ts/NDVI relationship and thelonger it remains steep, the more intense the drought as documented by direct measurementon the vegetation (Runyon et al., 1993). When derived from NOAA (AVHRR) satelliteover a 9 X 9 km area, the maximum steepness in slope was observed to occur on threedifferent sites about two month before drought stress actually halts photosynthesis andtranspiration (Goward et al., 1993). An alternative approach using synthetic aperture radarmay provide an independent evaluation of drought stress on vegetation (Way et al., 1991).

The nitrogen concentration in living and dead tissue is an important variable affectingrespiration from soil and from plants. The ratio of nitrogen to lignin in leaf litter is highlycorrelated with the rate that litter decays (Melillo et al., 1982). The OTTER project includeda test of whether the Airborne Visible/Infrared Imaging Spectrometer, AVRISS, couldpredict the chemical composition of foliage (Matson et al., 1993). Three-variable equationsdeveloped with step-wise regression techniques successfully predicted total nitrogenconcentrations when expressed as mg/m2 (r2 =0.86). Precise atmospheric corrections, bandfor band, were required, however, to calculate reflectance values accurately (Johnson et al.1993). A similar 3-variable equations showed some promise in predicting lignin (r2=0.92)concentrations in foliage (mg/m2 ) across the transect.

CONCLUSIONS

The success of any enterprise depends ultimately on the people involved and how theirtalents are employed. The 0 ITER project had a core of scientists with a range of skills inmodeling ecosystems, making direct estimates of system structure and function, acquiringremotely sensed observations, and in providing a means of storing and exchanging dataefficiently. Four concentrated field campaigns brought the core group together withcollaborators who tested additional methods within the framework of the project. Theavailability of a well defined model and clear goals at the start of the project made it easy tokeep priorities clear. Simultaneous measurements on the ground, from airborne platforms,

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and from satellites insured that scaling could proceed and integration fostered. As a result,we have better knowledge of the methods and their limits, the general need for atmosphericcorrections, the advantages of simultaneous coverage, and insights into how data fromvarious sensors can be combined in more fruitful ways to advance our understanding ofterrestrial ecosystems and their interactions with the biosphere.

ACKNOWLEDGEMENTS

I appreciate the extra effort made by all participants in the project to share the burdens ofintegration. Without their efforts I could not have summarized the main results of the studyfor this paper. Co-leader of the OTTER project, David Peterson, provided the initialsupport for a planning workshop and continued to lead the NASA portion of the projectthrough to its completion. His colleague, Mike Spanner, had the role of keeping all theflights operations organized. The work was supported financially and administratively byDiane Wickland and Anthony Janetos of the Biogeochemical Cycling Branch and by MelAverner of the Biospheric Research Program at NASA Headquarters. Finally, I thank mydaughter, Lise Waring, for providing professional editing of the manuscript.

REFERENCES

Cohen, WB„ and T.A. Spies. 1992. Estimating structural attributes of Douglas-fir/westernhemlock forest stands from LAND SAT and SPOT imagery. Rein_ Seas. Envir„41:1-18.

Eck, T. and D. Dye. 1991. Satellite estimation of photosynthetically active radiation at theEarth's surface. Rear. Sens Envir., 38:135-146.

McCreight, R.H., R.H. Waring, and S.N. Goward. 1993. Ecological remote sensing atOTTER: ultralight aircraft site-scale observations. Eco! Appl, (in review).

Johnson, L.F., C.A. Hlavka, and D.L. Peterson. 1993. Multivariate analysis of AVIRISdata for canopy biochemical determination along the Oregon transect.Rem.Sens.Envir, (in review).

Matson, P.A., L.F. Johnson, J.R. Miller, C.R. Billow, and R. Pu. 1993. Seasonalchanges in canopy chemistry across the Oregon transect: patterns and spectralmeasurements with remote sensing. Ecological Appl.,(accepted).

Melillo, J.M., J.D. Aber, and J.F. Muratore. 1982. Nitrogen and lignin control ofhardwood leaf litter decomposition dynamics Ecology, 63: 621-626.

Moghaddam, M., S. Durden, and H. Zebker. 1993. Radar measurement of forested areasduring OTTER. Rein. Sens. Envr, (in review).

Running, S.W. and J.C. Coughlan. 1988. A general model of forest ecosystem processesfor regional applications. I. Hydrologic balance, canopy gas exchange and primaryproduction processes. Eco! Modeling,42: 125-154.

Running, S.W. and S.T. Gower. 1991. FOREST-BGC, a general model of forestecosystem processes for regional applications. II. Dynamic carbon allocation andnitrogen budgets. Tree Physiol, 9:147-160.

Runyon, J., R.H. Waring, S.N. Goward, and J.M. Welles. 1993. Environmental limitson above-ground production: observations from the Oregon transect. EcologicalAppl,(in review).

Spanner, M., L. Johnson, J. Miller, R. McCreight, J. Runyon, P. Gong, and R. Pu.1993. Remote sensing of seasonal leaf area index across the Oregon transect.Ecological. Appl, (in review).

Waring, R.H., and J.F. Franklin. 1979. Evergreen coniferous forests of the PacificNorthwest. Science 204:1380-1386.

Way, J., J. Paris, M.C. Dobson, K. McDonald, F.T. Ulaby, J.A. Weber, S.L. Ustin,V.C. Vanderbilt, and E.S. Kasischke. 1991. Diurnal change in trees as observedby optical and microwave sensors: the EOS synergism study. IEEETransactions on Geosci and Rem. Sens.,29: 807-821.

Wu, Y. and A.H. Strahler. 1993. Remote estimation of crown size, stand density, andbiomass on the Oregon transect. Eco! Appl, (in review).