【摘要】 针对传统点位沉降监测的方法耗时耗力且难以大面积监测的问题，以某矿5302工作面为研究区域，利用无人机机载LiDAR技术获取2021年3月和2021年9月两期三维点云数据，通过点云解算、点云滤波、坐标转换等处理提取地面点云，采用Delaunay三角剖分算法进行DEM三角网构建，内插生成精度分别为0.071 m和0.128 m数字高程模型(DEM),通过ArcGIS进行矢量叠加和数据分析。将所提取的沉降结果分别与RTK测量数据和水准数据进行对比分析。实验结果表明，机载LiDAR可以很好地满足大范围沉降监测的需求，且能够较为精确反映沉陷区的沉陷状况，为沉降灾害的预防提供重要数据支撑。更多还原

【Abstract】 In view of the time-consuming and labor-intensive problems of traditional point settlement monitoring methods and the difficulty of large-scale monitoring, 5302 working face of a mine is taken as the research area in this paper. The UAV airborne LiDAR technology is used to obtain the three-dimensional point cloud data in March 2021 and September 2021. The ground point cloud is extracted through point cloud calculation, point cloud filtering, coordinate transformation and other processing. The Delaunay triangulation algorithm is used to construct the DEM triangulation network. The interpolation generation accuracy is 0.071 m and 0.128 m digital elevation model( DEM), respectively. The vector superposition is carried out by ArcGIS for data analysis. The extracted settlement results are compared with RTK measurement data and leveling data respectively. The experimental results show that airborne LiDAR can well meet the needs of large-scale subsidence monitoring, and can accurately reflect the subsidence status of subsidence areas, providing important data support for the prevention of subsidence disasters.更多还原