Abstract:
The Huanghuaihai Coal Mine area is mostly a high phreatic mining area.Coal mining causes surface subsidence and large amount of water in the depression.At the same time, there are problems such as sharp decline in cultivated land area, low land output rate and ecological imbalance, which seriously affects the sustainable use of resources and social economy.In today's rapid development of industrialization and urbanization in China, it is urgent to reveal the succession laws of water and soil resources and solve the problem of revitalization of water and soil resources in coal mining and subsidence areas.This paper takes the Peixian mining area in Xuzhou as the research object, and uses the D-InSar two-track differential method to extract the surface subsidence information from the ALOS PALSAR image.Based on the IDL platform visual programming, the random forest algorithm is selected and implemented, and the image spectrum and texture are introduced, thus, the high-resolution remote sensing images of Peibei mining area is classified.Combined with subsidence information and classification information, the water area is further divided into natural and collapsed waters.Using ANN-CLUE-S model, the water and soil spatial patterns are simulated in three different scenarios for 2030 in Peibei mining area, including natural development scenarios, sustainable development scenarios, and economic development scenarios, which provides a basis for government decision-making and related planning.