A Study on Historical Big Data Analysis of Surface Ecological Damage in the Coal Mining Area of Lvliang City Based on Two Mining Modes
Quanzhi Li,
Zhenqi Hu (),
Fan Zhang,
Yanwen Guo and
Yusheng Liang
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Quanzhi Li: School of Geosciences & Surveying Engineering, China University of Mining & Technology, Beijing 100083, China
Zhenqi Hu: School of Geosciences & Surveying Engineering, China University of Mining & Technology, Beijing 100083, China
Fan Zhang: School of Geosciences & Surveying Engineering, China University of Mining & Technology, Beijing 100083, China
Yanwen Guo: School of Environment Science & Spatial Informatics, China University of Mining & Technology, Xuzhou 221116, China
Yusheng Liang: School of Geosciences & Surveying Engineering, China University of Mining & Technology, Beijing 100083, China
Land, 2024, vol. 13, issue 9, 1-27
Abstract:
Coal mining inevitably causes damage to the surface ecological environment. In response to the characteristics of multiple factors, wide scope, and long time series of surface ecological environment damage in coal mining subsidence areas, how to integrate multiple data sources and monitoring methods to achieve monitoring and trend analysis of ecological damage throughout the entire mining cycle still needs to be studied. In addition, the 110 mining method provides an innovative method for underground coal mining to reduce its surface ecological damage, but the differences in surface damage between the two mining modes and the effectiveness of the 110 method in realizing surface ecological damage-reducing mining still need to be studied in depth. Therefore, this study takes the surface ecological damage in the mining area of Lvliang City, a typical resource city in Shanxi Province, China, as the object. It establishes a four-in-one “Satellite–UAV–Ground–Underground” information monitoring method, proposes a historical big data evolution analysis method, constructs three spatial scales of historical big databases, clarifies the current situation and development trend of damage in coal mining areas in Lvliang City and explores the differences in surface ecological environment damage characteristics in coal mining areas based on the 121 and 110 mining methods. The results show that: (1) The existing coal mining subsidence area in Lvliang City is as high as 92,191.47 hectares, and it is expected to continue to increase to 130,739.55 hectares in the future 2035, with a growth rate of 41.812%, which realizes the goals of mapping the current situation, retracing the history and predicting the future of the ecological damage of the surface in Lvliang City. (2) The surface NDVI of the 110 working face is restored to the average level of the mining area faster than that of the 121 working face. The surface crack width, step displacement, length, distribution density, and surface settlement height of the 110 working face are all smaller than those of the 121 working face. It has been verified that the unique top-cutting and swelling filling effect of the 110 methods can effectively reduce the ecological damage caused by coal mining subsidence. And its widespread application can effectively realize the ecological environmental protection of the coal mine area and contribute to the high-quality development of the coal industry in Lvliang City.
Keywords: ecological damage in mining areas; 110 mining method; “Satellite–UAV–Ground–Underground” monitoring method; historical big data (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)
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