Utility of ASTER and Landsat for quantifying hydrochemical concentrations in abandoned gold mining

Abstract

The effect of mining on water resources is severe and requires careful monitoring and management. Remote sensing has been used to characterize water quality indicators in efforts to fight mine-induced contamination. Much focus has however been placed on producing a qualitative classification of water qualities. Moreover, the number of variables considered in most studies is relatively small for a large number of hydrochemical constituents common in water bodies associated with gold mining activities. This study is aimed at quantifying a comprehensive list of field- and laboratory-measured chemical constituents of water samples from abandoned mines using remotely-sensed data. Akaike's Information Criterion was used to estimate each of the constituents using statistical values derived from individual bands of ASTER and Landsat data as predictors. Fairly good accuracies were obtained for constituents such as redox potential (Eh), major anions and cations. In contrast, trace elements correlated poorly with ASTER and Landsat bands, due mainly to a sampling anomaly. The performances of the two images in estimating the constituents were comparable. These findings suggest the potential of multispectral, moderate spatial resolution remote sensing for quantifying different hydrochemical properties of water bodies in mining environments. Further studies are however encouraged to enhance accuracies and reliability using a greater number of samples than was used in this study to capture the variability present in the population.