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This work aims to assess geobotanical anomalies related to high-sulfidation gold mineralization in terranes covered by almost virgin tropical rain forests located in the Tapajos gold province, northern Brazil. Landsat-5 TM data were processed using recently developed algorithms tailored to enhance both specific and anomalous vegetation spectral responses. The method consists of a four-stage successive concentration of information and reduction of data dimensionality, as follows: (1) spectral indexes are prepared to enhance responses of the vegetation characteristics, such as pigments and leaf moisture; (2) a principal component analysis (PCA) is applied on the set of indexes; (3) another PCA is applied to the original NIR and SWIR bands (SWIR; TM 4, 5, and 7), thus obtaining a PC1 as a texture-rich albedo image; and (4) a low-pass proportional convolution filter is applied to selected principal component images derived in the second step. The final product yielded through this technique indicates the presence of differentiated vegetation covers. In the study area, field information showed a near-perfect spatial correlation between color classes highlighted in this Landsat image product and hydrothermal alteration facies identified in outcrops. Although the product is unable to provide direct indication of any rock type, minerals, or presence of hydrothermal alteration, it proved suitable to outline areas where geobotanic anomalies associated to mineralogical variations occur. The method and its products are here considered an important aid for exploration planning and follow-up investigations in the field in terranes covered by equatorial forests.

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