杨耘, 江万成, 任超锋, 马正龙, 蒲禹池, 焦宇航. 倾斜影像辅助的无人机载LiDAR高陡边坡形变监测[J]. 红外与激光工程, 2023, 52(2): 20220373. DOI: 10.3788/IRLA20220373
引用本文: 杨耘, 江万成, 任超锋, 马正龙, 蒲禹池, 焦宇航. 倾斜影像辅助的无人机载LiDAR高陡边坡形变监测[J]. 红外与激光工程, 2023, 52(2): 20220373. DOI: 10.3788/IRLA20220373
Yang Yun, Jiang Wancheng, Ren Chaofeng, Ma Zhenglong, Pu Yuchi, Jiao Yuhang. Deformation monitoring of high and steep slopes with UAV LiDAR technology assisted by oblique images[J]. Infrared and Laser Engineering, 2023, 52(2): 20220373. DOI: 10.3788/IRLA20220373
Citation: Yang Yun, Jiang Wancheng, Ren Chaofeng, Ma Zhenglong, Pu Yuchi, Jiao Yuhang. Deformation monitoring of high and steep slopes with UAV LiDAR technology assisted by oblique images[J]. Infrared and Laser Engineering, 2023, 52(2): 20220373. DOI: 10.3788/IRLA20220373

倾斜影像辅助的无人机载LiDAR高陡边坡形变监测

Deformation monitoring of high and steep slopes with UAV LiDAR technology assisted by oblique images

  • 摘要: 针对高海拔峡域地形地貌环境下基于轻小型无人机载LiDAR对高陡边坡激光点云扫描数据缺失导致DEM重建及形变分析精度低的问题,优化设计了一种垂直于山脊线、变高飞行的无人机点云/多视影像数据采集,以及影像密集匹配点云辅助下LiDAR三维激光点云的滑坡群DEM重建方案,实现了复杂地形地貌下LiDAR点云数据安全、高效的采集,改善了高陡边坡DEM重建及形变监测的精度和完整性。该方法基于迭代最邻近点算法,将倾斜影像生成的点云数据与同期获取的LiDAR点云数据配准和融合,实现了LiDAR点云数据缺失补偿,进而构建出完整、高精度的DEM,并与往期倾斜影像生成的DEM进行差分,对三个典型滑坡体进行了高程形变分析。以青海龙羊峡水电站的高陡边坡滑坡群为研究区,利用实测的GNSS地面控制点进行实验验证,得出结论:融合后的LiDAR点云精度为0.063 m,比融合前提高了0.018 m;重建的三个典型滑坡体的DEM高程精度为0.08 m,提升了边坡DEM重建的完整性和精度;对三个典型滑坡体2018、2021年两期高程形变分析,表明:滑坡群中多个边坡发生不同程度的土体滑动,高程方向的形变高达50多米,滑坡群形变量大。

     

    Abstract: Aiming at the problem of low accuracy of DEM reconstruction and deformation analysis due to the lack of data during the scanning of high and steep slope point cloud based on light and small unmanned airborne LiDAR in the topographic environment of high-altitude gorge, this paper proposed an optimized data acquisition scheme using UAV image/point cloud data acquisition of high and steep slope flying perpendicular to the ridge, and DEM reconstruction scheme using UAV LiDAR point cloud with the aid of dense point cloud derived from multi-view oblique images. The accuracy and integrity of DEM reconstruction of high and steep slope and the accuracy of landslide deformation measurement in different periods have been improved. This method uses the point cloud data generated from the collected tilted image and the LiDAR point cloud data of the same period, in order to compensate the LiDAR point cloud missing data based on the iterative nearest neighbor point algorithm. Then, high-precision DEM products of landslides are constructed using the compensated LiDAR point cloud; Finally, the deformation of the landslides in elevation direction is obtained by comparing the current DEM with the DEM generated from the oblique images acquired in the past. Taking the landslides located at high and steep slopes of Qinghai Longyangxia Hydropower Station as the study area, an experiment is carried out and verified using the measured GNSS ground control points. It is concluded that the accuracy of LiDAR point cloud after fusion is 0.063 m, which is 0.018 m higher than that before fusion. The elevation accuracy of the reconstructed DEM of three typical landslides is 0.08 m, which improves the completeness and accuracy of DEM of slopes. The deformation results of typical landslides in the area are obtained by a comparison of DEM from two different epochs. The conclusions can be drawn that many slopes in the landslide group have different degrees of soil sliding, and the deformation in the elevation direction is up to more than 50 m, heavy deformations happened to the landslides.

     

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