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Spatial variation of land-surface properties is a major challenge to ecological and biogeochemical studies in the Amazon basin. The scale dependence of biophysical variation (e.g., mixtures of vegetation cover types), as depicted in Landsat observations, was assessed for the common land-cover types bordering the Tapajos National Forest, Central Brazilian Amazon. We first collected hyperspectral signatures of vegetation and soils contributing to the optical reflectance of landscapes in a 600-km(2) region. We then employed a spectral mixture model AutoMCU that utilizes bundles of the field spectra with Monte Carlo analysis to estimate sub-pixel cover of green plants, senescent vegetation and soils in Landsat Thematic Mapper (TM) pixels. The method proved useful for quantifying biophysical variability within and between individual land parcels (e.g., across different pasture conditions). Image textural analysis was then performed to assess surface variability at the inter-pixel scale. We compared the results from the textural analysis (inter-pixel scale) to spectral mixture analysis (sub-pixel scale). We tested the hypothesis that very high resolution, sub-pixel estimates of surface constituents are needed to detect important differences in the biophysical structure of deforested lands. Across a range of deforestation categories common to the region, there was strong correlation between the fractional green and senescent vegetation cover values derived from spectral unmixing and texture analysis variance results (r(2) > 0.85, p < 0.05). These results support the argument that, in deforested areas, biophysical heterogeneity at the scale of individual field plots (sub-pixel) is similar to that of whole clearings when viewed from the Landsat vantage point. (C) 2003 Elsevier Inc. All rights reserved

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