Environmental degradation associated with coal mining is one of the serious environmental issues in South Africa that is expected to continue with increasing energy demands. Mapping and monitoring contamination in mining areas are necessary to guide rehabilitation activities. Rapid monitoring systems are needed to develop effective rehabilitation plans. The advent of multispectral remote sensing data has proven to be effective in mapping and detecting mine related soil contamination. An integrated approach of soil geochemistry and remotely sensed data to characterise contamination in Emalahleni coal fields is presented in this study. Aster data was acquired and several band combinations were developed to identify patterns and occurrence of soil contamination. For geochemical assessment, the Nemerow index and the pollution loading index were calculated to evaluate the mining activity contamination. The classified aster images showed that contamination varies with land use. Residential areas and mining areas showed similar trends of contamination. Geochemical results showed that iron, vanadium and chromium are the most abundant elements in the study area. The findings of contamination indices reveal that the overall level of metal contamination in the study area is between moderate to heavily contaminated. The most polluted areas are concentrated in mining areas and along major transport intersections. The ASTER band ratios for silica and clay phases correspond with classified contamination indices indicating that remote sensing can successfully be used to assess pollution.