利用不同点云滤波算法构建矿山开采沉陷模型的对比研究  

Comparative Study on Mining Subsidence Models Constructed by Different Point Cloud Filtering Algorithms

作　　者：张咪咪 柴成富 ZHANG Mi-mi;CHAI Cheng-fu(Xi'an Aerospace Hongtu Information Technology Co.,Ltd,Xi'an Shaanxi 710199,China;Aerial Photogrammetry and Remote Sensing Group Co.,Ltd(ARSC),Xi'an Shaanxi 710199,China;Enterprise Technology Center,Aerial Photogrammetry and Remote Sensing Group Co.,Ltd(ARSC),Xi'an Shaanxi 710199,China)

机构地区：[1]西安航天宏图信息技术有限公司,陕西西安710199 [2]中煤航测遥感集团有限公司,陕西西安710199 [3]中煤航测遥感集团有限公司企业技术中心,陕西西安710199

出　　处：《地矿测绘》2024年第3期22-26,共5页Surveying and Mapping of Geology and Mineral Resources

摘　　要：针对现有机载LiDAR点云滤波算法缺乏详细对比的问题,以西部矿区某工作面地表沉陷区为试验区,选择渐进形态学滤波、三角网渐进加密滤波和基于坡度阈值滤波3种经典的算法去噪,并分析了算法的适用性。试验结果表明,在地表起伏明显、植被稀疏的陕北矿区,采集的点云数据利用三角网渐进加密滤波得到去噪后的点云建模效果最优。试验结果可为矿区开采沉陷精细化建模提供重要的技术手段。Aiming at the lack of detailed comparison of existing airborne LiDAR point cloud filtering algorithms,a surface subsidence area in a western mining area was selected as the experimental area.Three classic algorithms,namely progressive morphological filtering,triangular network progressive encryption filtering,and slope threshold filtering,were selected for denoising,and the applicability of the algorithms was analyzed.The experimental results show that in the mining area of northern Shaanxi,where the surface fluctuation is obvious and the vegetation is sparse,the point cloud modeling effect after denoising is the best by using triangulation progressive morphological filtering.The test results can provide important technical means for fine modeling of mining subsidence in mining areas.

关 键 词：机载LIDAR 点云滤波 矿山开采沉陷 DEM叠加分析 

分 类 号：P23[天文地球—摄影测量与遥感]