干旱区生态环境知识资源中心

A stream of multitemporal SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data was extracted and analyzed over the Amazon region and surrounding land-community validation sites representing a wide range of vegetation conditions. The raw data was atmospherically-corrected for molecular scattering and ozone absorption and the resulting bidirectional reflectances were used to compute various ratio-based, orthogonal-based, aerosol resistant, and enhanced vegetation indices. Results were analyzed for both the tilted 20 degrees look angle of SeaWifs and the extrapolated nadir (0 degrees) look using a BRDF model. Various vegetation indices were analyzed to evaluate their usefulness for carbon modeling studies, discriminating canopy structure variations, and in depicting land-use/land cover changes in semi-arid cerrado, and high biomass rainforests (primary and secondary). Previous studies have indicated problems with vegetation indices in the Amazon region with respect to chlorophyll-saturation and asymptotic vegetation index behavior. The objectives of this work were to (1) prototype gridded vegetation map products for the EOS- MODIS (MODerate resolution Imaging Spectroradiometer) and ADEOS- Global Imager (GLI) sensors; (2) assess the utility of multiple vegetation indices over continental data fields; (3) analyze sensitivities over a global range of vegetation conditions (cerrado to rainforest); and (4) assess the relative, usefulness of SeaWifs data in depicting canopy structural and compositional differences across the Amazon region. We found the SeaWifs data to be highly useful in mapping the vegetation cover of the Amazon region. The various vegetation indices yielded very contrasting results in their ability to discriminate vegetation and land-use differences. We conclude that multiple indices are required to fully characterize the spatial/temporal variations of the Amazon region. 250 m pixel sizes.