HR: 14:30h
AN: B33A-03    [Abstracts]
TI: Remote Sensing of Miombo Woodland's Aboveground Biomass and LAI using RADARSAT and Landsat ETM+ Data
AU: * Ribeiro, N S
EM: nsr8s@virginia.edu
AF: Unviersity of Virginia, 291 McCormick Rd., Clark Hall, Charlottesville, va 22904, United States
AU: Saatchi, S S
EM: saatchi@congo.jpl.nasa.gov
AF: Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, United States
AU: Shugart, H H
EM: hhs@virginia.edu
AF: Unviersity of Virginia, 291 McCormick Rd., Clark Hall, Charlottesville, va 22904, United States
AU: Wshington -Allen, R A
EM:
AF: Unviersity of Virginia, 291 McCormick Rd., Clark Hall, Charlottesville, va 22904, United States
AB: Estimations of biomass are critical in Miombo Woodlands because they represent a primary source of food, fiber, and fuel for 340 million rural peoples and another 15 million urban dwellers in southern Africa. The purpose of this study is to estimate woody aboveground biomass and Leaf Area Index (LAI) in Niassa Reserve, northern Mozambique. The objective of this study is to use optical and microwave satellite data with contemporaneous field data to estimate biomass and LAI. Fifty field plots were surveyed across the Niassa Reserve for biomass and LAI in July and December 2004, respectively. Remote sensing data consisting of RADARSAT backscatter (C- band, ë=5.6 cm) and a June 2004 Landsat ETM+ were acquired. Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), and a land-cover map (72% total accuracy) were derived from the Landsat scene. Field measurements of biomass and LAI correlated with Radarsat backscatter (Rsqbiomass=0.45, RsqLAI = 0.35, P<0.0001 ), NDVI (Rsqbiomass =0.15, RsqLAI=0.14-, p <0.0001 ) and SR (Rsqbiomass=-0.14, RsqLAI= 0.17, p <0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 +0.074*radarsat+1.56*SR, Rsq=0.53) and LAI (LAI= -0.66+0.01*radarsat+0.22*SR, Rsq=0.45). The addition of NDVI did not improve the model. Forest biomass and LAI maps were then produced for Niassa Reserve with an estimated peak total biomass of 18 kg/hm2 and a mean LAI of 2.8 m2/m2. In the east both biomass and LAI are lower than the western Niassa Reserve.
DE: 1630 Impacts of global change (1225)
DE: 1631 Land/atmosphere interactions (1218, 1843, 3322)
DE: 1632 Land cover change
DE: 1640 Remote sensing (1855)
SC: Biogeosciences [B]
MN: 2007 Joint Assembly