Monitoring Surface Deformation Research In Mining Area By Integrating UAV LiDAR And Orthophoto

China is a major player in mining industry,and the exploitation of mineral resources brings indispensable economic benefits in the long course of its development.However,subsequent issues of exploitation in mining regions,including surface deformation and cracking house,are posing grim threats to people’s lives and property.To this end,it carries important research value and practical significance to develop and improve deformation monitoring approach on the ground of mining areas,establish warning system for ground deformation and evaluate property loss caused by surface deformation.Monitoring technology in mining areas based on the UAV platform enjoys merits of being cost-effective and efficient.Moreover,UAV Li DAR can capture highly-accurate ground geometric information,and orthophoto can obtain ground texture information.The strengths of these two methods,if properly combined and leveraged,can contribute to improving performance on monitoring surface deformation.However,two major problems remain to be resolved in current researches.(1)It is hard to pinpoint grid step for meshing point cloud in vertical surface deformation calculation.(2)The feature extraction of Li DAR point cloud based on single method cannot do justice to the horizontal deformation feature in mining areas.In this connection,main research contents and major new points of this article are as follows:(1)This article proposed point-cloud vertical deformation monitoring method in mining areas by considering the optimal grid step.Concerning the difficulties in determining grid step for meshing point cloud in vertical deformation calculation,this article explored into performance variation of Mesh to Mesh(M2M),P2P(Point to Point),Cloud to Mesh(C2M)approaches under different grid steps.This article then proposed the pointcloud vertical deformation monitoring method in mining areas by considering the optimal grid step.Results show that the overall average deviation of the proposed method is about 6.2 cm,which represents about1.9 cm reduction compared with these traditional methods,and vertical deformation is around 80-120 cm in working areas.(2)This article proposed horizontal monitoring method on the surface of mining areas by integrating multi-source features.Given inadequate features extracted by a single method results in low coverage on measuring horizontal deformations in mining areas,the article makes comparison of the applicability of different feature extracted algorithms.This article also proposed a horizontal monitoring method on the surface of mining areas by integrating multi-source features,and applied on the Nanmiao mining areas.Results show that the number of valid feature points extracted by the proposed method is about 5259,while that number posted by the single traditional method is about 3443.The proposed method can improve coverage,while not compromising monitoring results.The results based on the proposed method shows that the south-north displacement in mining areas mainly direct towards the north with an average displacement distance of 21.1 cm with about 1.1 cm deviation.The east-west deformation head towards the center of the working area with about 3.5cm overall deviation in east-west direction.The eastern displacement distance posts 19.4 cm and the western displacement distance is about 10.1 cm.