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Processing Methodology Based on ASTER Data for Mapping Mine Waste Dumps in a Semiarid Polysulphide Mine District

Abstract. The aim of this work is to present a simple, economic, and efficient methodology based on the use of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to map areas of mining waste composed of heterogeneous mineral mixtures. This methodology has been applied to the District of Santa María de la Paz, Mexico, to detect different mineral phases that have been previously characterized. The methodology consists of techniques such as band ratioing, Normalized Difference Tailings Index (NDTI), and Spectral Angle Mapper (SAM) classification. Experimentation with the SAM classification has established a minimum threshold of 0.08 radians for the mapping of mining waste and tailings impoundments. The results of this analysis indicate that the different techniques applied to ASTER images do not show the same level of accuracy for all waste dumps. In this study, the best technique for mapping the different mine wastes is the ferrous iron ratio, which features an overall accuracy of 93.25 % and a kappa coefficient of 0.86. The accuracy of the results suggest that the proposed methodology can be used in the detection of mine waste in mining districts that have not been fully characterized, especially in countries with a large amount of abandoned mining waste.