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.

A self-organizing map (SOM) approach has been used to provide an integrated spatial analysis and classification of airborne geophysical data collected over the Brazilian Amazon. Magnetic and gamma ray spectrometric data were used to extract geophysical signatures related to the spatial distribution of rock types and to produce a geologic map over the prospective Anapu-Tuerê region. Particular emphasis was given to discriminating and identifying rock types, and the processes related to gold mineralization, which are known to occur in the Anapu-Tuerê region. SOM was able to identify and map distinctive geophysical signatures related to the various geologic units identified on the published geologic map. Furthermore, SOM was able to identify and enhance very subtle signatures derived jointly from the magnetic and gamma ray spectrometric data that could be related to geologic processes present in the area. These results demonstrate the effectiveness of using SOM as a tool for geophysical data analysis and for semiautomated mapping in regions such as the Amazon.

This paper describes the use of Landsat Thematic Mapper (TM) imagery for geological mapping in a tectonically-complex area of south-east Spain. The terrain includes the metamorphic basement rocks of the Betic Cordillera and the sedimentary strata of an intermontane basin. TM bands 1, 3 and 5 were used to produce a colour composite. Experimentation showed that this was the most effective band combination to discriminate rock types in the semi-arid study region. A combination of spectral and textural characteristics was used to identify and map rock types in the Nevado-Filabride and Alpujarride basement complexes, sedimentary strata in the Neogene Tabernas-Sorbas Basin and Quaternary drift deposits. Structural features were best shown by digital convolution using a directional filter. The enhanced images revealed a previously unreported fault and fracture belt on the northern side of the Tabernas Basin. The geological interpretation of enhanced TM imagery was locally checked in the field.