Semiautomated geologic mapping using self-organizing maps and airborne geophysics in the Brazilian Amazon

Abstract

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.