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Abstract
Subsidence data acquisition methods are crucial to mining subsidence research and an essential component of achieving the goal of environmentally friendly coal mining. The origin and history of the existing methods of field monitoring, calculation, and simulation were introduced. It summarized and analyzed the main applications, flaws and solutions, and improvements of these methods. Based on this analysis, the future developing directions of subsidence data acquisition methods were prospected and suggested. The subsidence monitoring methods have evolved from conventional ground monitoring to combined methods involving ground-based, space-based, and air-based measurements. While the conventional methods are mature in technology and reliable in accuracy, emerging remote sensing technologies have obvious advantages in terms of reducing field workload and increasing data coverage. However, these remote sensing methods require further technological development to be more suitable for monitoring mining subsidence. The existing subsidence calculation methods have been applied to various geological and mining conditions, and many improvements have already been made. In the future, more attention should be paid to unifying the studies of calculation methods and mechanical principles. The simulation methods are quite dependent on the similarity of the model to the site conditions and are generally used as an auxiliary data source for subsidence studies. The cross-disciplinary studies between subsidence data acquisition methods and other technologies should be given serious consideration, as they can be expected to lead to breakthroughs in areas such as theories, devices, software, and other aspects.
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Details

1 Taiyuan University of Technology, College of Mining Engineering, Taiyuan, China (GRID:grid.440656.5) (ISNI:0000 0000 9491 9632)
2 Zhejiang University, School of Public Affairs, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X)
3 Shanxi University of Finance and Economics, School of Public Administration, Taiyuan, China (GRID:grid.464425.5) (ISNI:0000 0004 1799 286X)