Research on DEM multiple filtering method for mining subsidence

Abstract

Aiming at the problems of long cycle time and large workload of traditional surface movement monitoring methods, the method of acquiring ground point clouds and constructing subsidence DEM through UAV LiDAR and point cloud filtering enables surface subsidence monitoring fast and efficient. Because of the subsidence DEM models constructed by existing point cloud filtering and interpolation algorithms still cover noise, which limits the popularity of this technology in mining areas, therefore, it is significant to further study the removal method of subsidence DEM noise, compare and analyze the multiple filtering and classical filtering techniques. Experimental analysis results show that the median filter combined with Wiener filter has the best denoising effect among several denoising methods, which can keep the details of the subsidence basin and meet the basic requirements of surface deformation monitoring in mining areas.

Keywords

• unmanned aerial vehicle lidar
• surface subsidence
• point cloud filtering
• subsidence dem
• multi-filtering