Application of hyperspectral remote sensing for environment monitoring in mining areas

Abstract

Environmental problems caused by extraction of minerals have long been a focus on environmental earth sciences. Vegetation growing conditions are an indirect indicator of the environmental problem in mining areas. A growing number of studies in recent years made substantial efforts to better utilize remote sensing for dynamic monitoring of vegetation growth conditions and the environment in mining areas. In this article, airborne and satellite hypersectral remote sensing data—HyMap and Hyperion images are used in the Mount Lyell mining area in Australia and Dexing copper mining area in China, respectively. Based on the analyses of biogeochemical effect of dominant minerals, the vegetation spectrum and vegetation indices, two hyperspectral indices: vegetation inferiority index (VII) and water absorption disrelated index (WDI) are employed to monitor the environment in the mining area. Experimental results indicate that VII can effectively distinguish the stressed and unstressed vegetation growth situation in mining areas. The sensitivity of VII to the vegetation growth condition is shown to be superior to the traditional vegetation index—NDVI. The other index, WDI, is capable of informing whether the target vegetation is affected by a certain mineral. It is an important index that can effectively distinguish the hematite areas that are covered with sparse vegetation. The successful applications of VII and WDI show that hyperspectral remote sensing provides a good method to effectively monitor and evaluate the vegetation and its ecological environment in mining areas.