Application of hyperspectral remote sensing for environment monitoring in mining areas |
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Authors: | Bing Zhang Di Wu Li Zhang Quanjun Jiao Qingting Li |
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Institution: | (1) Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian, Beijing, 100094, People’s Republic of China;(2) Graduate University of Chinese Academy of Sciences, 19A Yuquanlu, Beijing, 100049, People’s Republic of China |
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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. |
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