LAUSR

Zoning for the eco-geological environment (EGE) aims to protect and improve the regional ecological environment. It is the basis for evaluating the ecological characteristics of a mining area prior to mining activities and has the purpose of implementing water-preserved mining according to zoning type. In this study, four EGE types were proposed following field investigation in the Yushenfu mining area: oasis type with phreatic water and bottomland in desert (OTPWBD), oasis type with surface water and valley river (OTSWVR), loess gully type with surface runoff (LGTSR), and regional deep groundwater enrichment type (RDGET). Nine EGE evaluation indices were selected: rainfall, evaporation capacity, Luohe formation thickness, surface elevation, Sara Wusu aquifer water abundance, surface lithology, topography, slope, and normalized difference vegetation index (NDVI). Remote sensing technology and geographic information systems were first used to generate the evaluation index thematic maps. Then, the weight of each evaluation index was determined based on an analytic hierarchy process (AHP). Third, the index weight was used to form an improved weighted fuzzy C s clustering algorithm, and EGE zones were assigned using the MATLAB computing platform. For comparison, the AHP was also adopted for EGE zoning and a map of zoning differences was obtained. Finally, EGE field surveys of typical mines were carried out, which verified that EGE zoning using fuzzy clustering was accurate and reasonable.