复杂地形条件下多密度级无人机LiDAR点云DEM精度研究——以2022年北京冬奥会延庆赛区为例  

Research on Precision Level of DEM Based on Multi-density UAV LiDAR Point Cloud Data Under Complex Terrain Conditions——Take the Yanqing Area of the 2022 Beijing Winter Olympics as An Example

作　　者：霍芃芃 王梓琪 闫旭 HUO Pengpeng;WANG Ziqi;YAN Xu(Beijing Institute of Surveying and Mapping,Beijing 100038,China;Beijing Key Laboratory of Urban Spatial Information Engineering,Beijing 100038;China School of Geomatics and Urban Spatial Informatics,Beijing University of Civil Engineering and Architecture,Beijing 100044,China)

机构地区：[1]北京市测绘设计研究院,北京100038 [2]城市空间信息工程北京市重点实验室,北京100038 [3]北京建筑大学测绘与城市空间信息学院,北京100044

出　　处：《北京测绘》2021年第10期1272-1277,共6页Beijing Surveying and Mapping

基　　金：城市空间信息工程北京市重点实验室开发基金(2020214)。

摘　　要：为进一步提升复杂地形条件下无人机激光雷达(Light Detection and Ranging,LiDAR)点云数据构建数字高程模型的效率与精度,以2022年北京冬奥会延庆赛区场馆建设用地为实验区,按照不同抽稀比例,对实验区原始无人机激光雷达点云中分类出的地面点数据进行抽稀处理,利用克里金插值算法对不同密度地面点数据进行插值处理,结合高程中误差、平均绝对误差对生成的数字高程模型进行双重精度评定,得出以下结论:对于复杂地形而言,随着点云数据密度的下降,数字高程模型建模效率明显提升,但地形特征逐渐模糊,数据精度级别逐级降低,其中高程中误差由0.381 m增大至1.914 m,平均绝对误差值由0.335 m增大至1.357 m。在满足精度要求的前提下,对LiDAR点云数据进行适度抽稀处理,可保障生产成本与时效。In order to further improve the efficiency and accuracy of producing DEM data with UAV LiDAR point cloud under complex terrain conditions,this paper took the construction land of 2022 Beijing Winter Olympic Games as the experimental area.Different thinning ratio was appliedto extract the ground point data.Then Kriging interpolation algorithm was utilized to process the data.Double precision evaluation of the DEM data was carried out by Mean Square Error of Height and Mean Absolute Deviation.The following conclusions were drawn:for complex terrain,with the decrease of point cloud data density,the terrain features of DEM data were gradually fuzzy,and the data precision level was gradually reduced.TheMean Square Error of Heightwas increased from 0.381 m to 1.914 m,and the Mean Absolute Deviationwas increased from 0.335 m to 1.357 m.On the premise of meeting the accuracy requirements,the proper dilution processing of the LiDAR point cloud data could guarantee the production cost and timeliness.

关 键 词：数字高程模型 无人机激光雷达点云 抽稀算法 抽稀比例 精度评定 

分 类 号：P258[天文地球—测绘科学与技术]