High-Precision 3-D Deformation Information Extraction of Mine Surfaces Using UAV LiDAR Technology

Accurate monitoring of ground subsidence caused by underground coal mining is crucial for environmental protection. This article proposes a correction method for coal mining subsidence, termed subsidence correction based on horizontal displacement (SCHD), utilizing unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) technology. This method leverages the strengths of image subpixel correlation technology in obtaining high-precision horizontal displacement information while addressing the limitations of the traditional digital elevation model (DEM) differential-difference of difference (DOD) method, which often yields incomplete and inaccurate deformation data. Through simulation experiments and field verifications, we quantitatively analyze the effects of surface slope, the angle between the aspect and the horizontal displacement vector, and the magnitude of horizontal displacement on subsidence modeling accuracy. We validate the reliability of the multiimages correspondances par méthodes automatiques de corrélation (MicMac) image subpixel correlation technique for extracting horizontal displacement information from the ground surface before and after coal mining, and we correct the subsidence errors introduced by neglecting horizontal displacement using the proposed SCHD method. The results indicate that overlooking horizontal displacement can lead to significant overestimations or underestimations of vertical deformation, with error magnitude closely related to the aforementioned topographic parameters and displacement characteristics. The high-precision horizontal displacement information obtained through the image subpixel correlation technique meets subsidence monitoring requirements. The SCHD method effectively reduces subsidence modeling errors and improves monitoring accuracy by 15.6%–40%, achieving centimeter-level precision. This study underscores the significant impact of horizontal displacement on monitoring coal mining subsidence, demonstrating that the SCHD method enhances the accuracy of such monitoring and provides a robust technical approach for extracting detailed 3-D deformation information from mining area surfaces.