Comparison of multi-source satellite data for quantifying water quality parameters in a mining environment

摘要: Abstract Population growth and associated anthropogenic activities such as mining are posing a major threat to water resources. Remote sensing provides valuable information for assessing monitoring quality quantity, thus supports sustainable management. Several studies have demonstrated the utility of various remote techniques quantifying parameters, however, more needs be done exploit growing number satellite sensors available public. The main objective this study was evaluate performances individual combined bands Landsat 8 OLI, Sentinel-2 MSI, ASTER SPOT 6 data predictors parameters open bodies in area. We applied all-subsets regression approach explore all possible candidate models from which selection made based on Akaike’s Information Criterion (AIC), coefficient determination (adjR2) Root-Mean-Squared-Error (RMSE). Two secondary objectives that make use products were added study. This included comparison parsimonious model containing few with ranked best but predictors; consisting similar across per parameter. In general, yielded promising estimation accuracies, particularly SAR, permanent hardness cations (RMSE   0.95) most while similarity decreased predicting increased. Furthermore, similarities obtained between compared other pairs, indicating potential replacing one absence other. findings showed advantage commonly used remotely-sensed estimating, by extension monitoring, bodies. addition, results revealed few, specific carry relevant characterise considered recommend different seasons, considering need monitor throughout year.