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Ecological restoration of coal mining subsidence area is of great significance to improve the ecological and living environment, enrich the supply of ecological products, promote the green transformation of resource-based cities and the high-quality development of urban and rural areas. This paper combs the significance of ecological restoration in coal mining subsidence area to promote the high-quality development of urban and rural areas, systematically expounds the realization path of ecological restoration to promote urban-rural spatial integration, cultural integration, economic integration and social integration development by taking Pan’an Lake coal mining subsidence area as a case. Finally, the high-quality development evaluation index system of coal mining subsidence area based on ecological restoration is put forward, and the prospect of ecological restoration and high-quality development in coal mining subsidence area are discussed.

Water body is one of the most active and important earth resources, and which has a profound impact on the natural system and human society. In order to acquire surface water body information quickly, accurately and efficiently, the method of water body information extraction using remote sensing imagery has attracted the attention of many searchers. On the basis of sorting out relevant research results of water body information extraction using remote sensing imagery, this paper proposed the method of water body information extraction based on the tasseled cap transformation for complex environments such as shadow and dense vegetation. First, radiometric calibration and atmospheric correction were carried out for remote sensing images. Then, the tasseled cap transformation was performed to obtain the greenness component and wetness component. Finally, the model of water body information extraction based on the tasseled cap transformation was constructed, and the water body information was extracted. In a region of Hunan province, China, the experiment using GF-1 WFV remote sensing image shows that the extracted water body information has a clear boundary and complete shape, and the Kappa coefficient, overall accuracy and user accuracy are 0.89, 92.72%, and 88.04%, respectively.