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SATELLITE REMOTE SENSING AND GROUND-BASED ESTIMATES OF FOREST BIOMASS AND CANOPY STRUCTURE
Citation:
Pilant, A, J. Iiames, R S. Lunetta, K Endres, AND T E. Lewis. SATELLITE REMOTE SENSING AND GROUND-BASED ESTIMATES OF FOREST BIOMASS AND CANOPY STRUCTURE. Presented at Science Forum 2003, Washington, DC, May 5-7, 2003.
Impact/Purpose:
Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.
Description:
MODIS (Moderate Resolution Imaging Spectroradiometer) launched in 1999 is the first satellite sensor to provide the kind of data necessary to intensively probe the global landscape for LAl. Because it is a new sensor, its data products must be validated with ground data. This research then has two goals;
1) Validate MODIS LAI and NDVI (Nom1alized Difference Vegetation Index) estimates using field measurements;.
2) Develop improved methods for land-cover mapping and landscape change detection using remote sensing.
We are using an emerging technology to measure LAl in the field: combined digital hemispherical photography and sunfleck profiling. This methodology captures geometric characteristics of canopy architecture that control the reflected sunlight signals received by
satellite sensors. We have established a network of six validation sites in the Albemarle~Pamlico Basin of North Carolina and Virginia and lead a collaboration to collect the necessary data. NASA is providing satellite imagery, Duke University and North Carolina State University are providing access to well-studied field locales for instrument validation, industry partners Westvaco and International Paper provide access to forest land, as are the States of North Carolina and Virginia. In this poster we present the methodology used and example imagery showing trends in forest LAI.