融合LiDAR点云与无人机影像的滑坡动态监测技术  

Landslide dynamic monitoring technology by integrating LiDAR point cloud and UAV image

作　　者：徐宇翔 胡庆武[1] 段延松[1] 李加元[1] 艾明耀[1] 赵鹏程[1] XU Yuxiang;HU Qingwu;DUAN Yansong;LI Jiayuan;AI Mingyao;ZHAO Pengcheng(School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China)

机构地区：[1]武汉大学遥感信息工程学院,湖北武汉430079

出　　处：《测绘通报》2024年第8期42-47,共6页Bulletin of Surveying and Mapping

基　　金：国家重点研发计划(2021YFB2600401);国家自然科学基金(42371439)。

摘　　要：滑坡是一种危害性较大的自然灾害,如何对其进行高效准确的监测具有重要研究价值和实际意义。利用LiDAR、无人机航空摄影等技术进行滑坡监测,可以快速、安全、精确地获取滑坡区域地面信息。本文提出了融合LiDAR点云的无人机影像滑坡动态监测方法。首先,利用点云和影像获取高质量DSM;然后,设计一种基于不规则三角网和坡度融合的滤波算法,滤除DSM中低矮植被,生产高精度DEM;最后,通过对两期DEM进行差分,实现对滑坡区域的动态监测。以黄登水电站附近边坡区域的LiDAR数据与无人机影像数据开展试验,结果表明,采用本文方法进行滑坡动态监测可以直观地判断滑坡地形变化和位移趋势,具有一定的应用前景。Landslide is a kind of natural disaster with great harm.How to monitor it efficiently and accurately has important research value and practical significance.Using the technology of LiDAR and UAV aerial photography in landslide monitoring can quickly,safely and accurately obtain ground information of landslide area.In this paper,a dynamic monitoring method of UAV image landslide based on LiDAR point cloud is proposed.Firstly,point cloud and images are used to obtain high-quality DSM reliably,and then a filtering algorithm based on irregular triangulation network and slope fusion is designed to filter out low vegetation in DSM and produce high-precision DEM.Finally,the dynamic monitoring of landslide area is realized through the difference of two DEM.In this paper,the LiDAR data and UAV image data of a slope area near Huangdeng hydropower station are used to carry out experiments.The results show that the landslide dynamic monitoring method intuitively judges the change of landslide topography and has a certain application prospect.

关 键 词：LIDAR数据 无人机影像 数据融合 滑坡监测 

分 类 号：P23[天文地球—摄影测量与遥感]