MULTISPECTRAL and HYPERSPECTRAL SATELLITE DATA for ALTERATION MAPPING USING PARTIAL-SUBPIXEL ALGORITHM in AN UNEXPLORED REGION

Abstract

The focus of this paper is to comparatively evaluate the performance of ASTER and Hyperion data for target detection of hydrothermal alteration zones associated with geothermal (GT) springs in an unexplored savannah region. The study employed the partial subpixel unmixing Mixture Tuned Match Filtering algorithm for spectral information extraction using the multispectral and hyperspectral satellite data. In both cases, image endmember spectra specifically for kaolinite, alunite, and illite and calcite zones were selected and extracted by using the Analytical Imaging and Geophysics (AIG)-developed processing methods. The results show that the Hyperion, despite its distortions, can effectively discriminate associated alteration zones better than ASTER. Consequently, Hyperspectral data and analysis are thus recommended for use in similar unexplored regions for GT resource detection and monitoring.