Synergistic Monitoring Framework for Mining Subsidence Under Thick Loose Layers by Integrating InSAR and UAV Photogrammetry
The surface subsidence caused by coal mining is a geological environmental disaster that restricts the sustainable development of mining areas. Traditional monitoring methods have limitations in long-term and high-precision observation. Therefore, this paper proposes a synergistic monitoring framework for mining subsidence under thick loose layers by integrating Interferometric Synthetic Aperture Radar (InSAR) technology and Unmanned Aerial Vehicle (UAV) photogrammetry. The research results show: (1) UAV photogrammetry can accurately obtain the large gradient deformation at the center of the subsidence basin, while InSAR has better accuracy at the basin edge. The proposed fusion method is significantly superior to a single method. (2) The parameters obtained by the probability integral method based on the fused data are in good agreement with the parameters obtained by leveling measurement data, and the relative error of the parameters is less than 4%. (3) The thick and loose-layered mining areas have the characteristics of larger subsidence, steeper gradient at the center, slow convergence at the edge, and wide influence range. This study provides a new approach for precise subsidence monitoring, and the revealed subsidence characteristics provide a scientific basis for disaster assessment and mining optimization in similar areas.