We present the results of an analysis that combines coarse and fine spatial resolution remote sensing data to reconstruct time series of nonforested area in a region of the Brazilian Amazon. We used a 10-year sequence (1989–1998) of Landsat Thematic Mapper data for one scene (∼30,000 km2) in Rondônia, Brazil, to parameterize a regression model that uses subsets of AVHRR GAC reflectance data. This model detected information on interannual changes in nonforested area with a combination of detail and coverage greater than would normally be available using either data set alone. Within this domain we retrieved nonforest cover fraction in a cross-validation test with coefficients of determination (R2) of 0.32 at 8–km resolution and 0.64 at 48-km resolution. At the 48-km resolution the model captures interannual variability and trends of fractional cover within individual pixels that changed considerably over the 10 years of this analysis. The results for this region suggest that retrospective analyses will benefit from further development of techniques combining AVHRR, TM, and other prior information.
Journal of Geophysical Research: Atmospheres
Digital Object Identifier (DOI)
Hagen, S. C., B. H. Braswell, S. Frolking, W. A. Salas, and X. Xiao, Determination of subpixel fractions of nonforested area in the Amazon using multiresolution satellite sensor data, J. Geophys. Res., 107 (D20), 8049, doi: ref="info:doi/doi:10.1029/2000JD000255">doi:10.1029/2000JD000255, 2002.
Copyright 2000 by the American Geophysical Union.