A Look at Amazon Basin Seasonal Dynamics with the Biophysical ...

Standardized remote sensing methodology for land-cover mapping in support ofLBA.D.A. Roberts 11Dept of Geography, University of California at Santa Barbara, Santa Barbara, CA 93106-4060,E-mail: dar@geog.ucsb.eduConsiderable uncertainty remains in our knowledge of human impacts inAmazonia. Important research questions include determining the rates of forestconversion and agricultural abandonment, the age structure and area of regeneratingforest and pasture and the area impacted by forest degradation due to selective logging,fragmentation and fire. Answers to these questions have regional and global implicationsin terms of biological diversity, hydrology, biogeochemistry and climate. Remotesensing, applied across multiple spatial and temporal scales, represents one of the mostviable means of mapping human impacts in Amazonia. However, to be most effective, itis critical that standardized tools are used, thus providing a means of comparison throughtime and across regions. Here I present an example of a standardized approach. I describea multistage process in which remotely sensed data are georectified to a common basemap, intercalibrated to remove atmospheric, instrumental and lighting differences, thendecomposed as mixtures of green vegetation, non-photosynthetic vegetation, shade andsoil using spectral mixture analysis. Spectral fractions are used to train a decision treeclassifier to map forest, pasture, second growth forest/crop and soil/urban using a singleset of decision rules. Transitions from forest to non-forest classes are used to estimaterates of forest clearing and map the age structure of non-forest classes. Changes in foreststructure associated with degradation are mapped at sub-pixel scales through the analysisof changes in shade, non-photosynthetic vegetation, green vegetation and soil followingdegradation.To illustrate the potential of such an approach I draw upon examples fromresearch in Rondonia, Manaus and Maraba, Brazil, in which Landsat MSS and TM dataare used to quantify land-cover dynamics over a period of up to 25 years. I discusslimitations of currently available data and the potential of new opportunities, such as theairborne deployment of AVIRIS as a means of improving interpretation of TM.