Monitoring of mining subsidence based on UAV photogrammetry technology

Intensive coal mining leads to ground subsidence, posing a significant threat to the lives, property, and ecological environment of the surrounding communities in mining areas. Therefore, efficiently obtaining high-precision subsidence data is particularly important. This paper focuses on a large mining height working face at Xinyi Coal Mine in Xin'an County, Luoyang City, and conducts subsidence monitoring in the mining area through UAV photogrammetry technology. The study optimizes the data processing workflow, including point cloud filtering, vegetation point removal, and DEM data overlay, to construct a subsidence basin model. In the research, Pegasus D2000 UAV equipped with SONY a6000 camera was used for multi-period aerial photography data collection, and EasyCalibrate software was employed for camera calibration to ensure high precision in image processing. By comparing classic filtering and interpolation algorithms, the study selected the most suitable point cloud processing algorithm for the area, effectively removing noise points and improving the accuracy of DEM construction. Ultimately, by comparing the aerial survey subsidence basin model with actual measured data, the precision of the model was verified, with a root mean square error of 0.024 meters, indicating that the optimized UAV photogrammetry technology can significantly enhance the precision of subsidence monitoring, which is of great importance for geological disaster assessment and prevention.