Integrated Processing and Imaging of Exploration Data: An Application of Fuzzy Logic

Abstract

Recently, Earth observation tools and geological exploration techniques have been developing rapidly, alongside significant advancements in computer technology and data processing capabilities. These developments encourage integrated multi-sensor, and multi-target observation of the Earth System environment, resulting in massive volumes of Earth science and geological exploration data. A number of new approaches for handling such large volumes of data have been proposed, including those based on classical Bayesian statistics and probability theory. However, fuzzy logic approximation of the spatial information (Earth science and geological exploration data) has been quick and effective for efficient and accurate analysis of complex geological exploration data and associated Earth system information. For more complex spatial reasoning, a combined single-stage fuzzy neural network approach has also been successfully applied, with future prospects of cascaded multi-stage fuzzy neural network systems. This chapter reviews some of the recent developments in the theoretical aspects of fuzzy logic and neural network models in Earth System science and geological application problems.