Principal component analysis (PCA) is an image processing technique that has been commonly applied to Landsat Thematic Mapper (TM) data to locate hydrothermal alteration zones related to metallic deposits. With the advent of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a 14-band multispectral sensor operating onboard the Earth Observation System (EOS)-Terra satellite, the availability of spectral information in the shortwave infrared (SWIR) portion of the electromagnetic spectrum has been greatly increased. This allows detailed spectral characterization of surface targets, particularly of those belonging to the groups of minerals with diagnostic spectral features in this wavelength range, including phyllosilicates (‘clay’ minerals), sulphates and carbonates, among others. In this study, PCA was applied to ASTER bands covering the SWIR with the objective of mapping the occurrence of mineral endmembers related to an epithermal gold prospect in Patagonia, Argentina. The results illustrate ASTER's ability to provide information on alteration minerals which are valuable for mineral exploration activities and support the role of PCA as a very effective and robust image processing technique for that purpose.