面向滩涂DEM构建的机载LiDAR点云滤波方法

The filtering method of airborne LiDAR point cloud for tidal flat DEM construction

在基于激光点云构建DEM的过程中,用于区分地面点和非地面点的点云滤波处理至关重要。本文面向基于机载LiDAR点云的沿海滩涂DEM高精度的构建需求,提出了一种机载LiDAR点云的改进坡度滤波算法。首先,采用统计异常值剔除法(SOR)去除原始机载LiDAR点云数据中的噪声;然后,利用规则格网的坡度和高程阈值,设计了适用于滩涂点云数据的地面点坡度滤波方法;最后,选取如东市长沙港的滩涂机载LiDAR点云作为试验数据,构建滩涂DEM,并进行精度检验。试验结果表明,利用本文方法处理后的LiDAR点云构建的DEM精度满足国家与行业标准的要求。

In the process of constructing DEM based on laser point cloud,point cloud filtering is very important to distinguish ground points and non-ground points.Considering the requirement of high-precision DEM construction based on airborne LiDAR point cloud for coastal tidal flat regions,the paper proposes an improved slope filtering algorithm of airborne LiDAR point cloud.Firstly,a statistical outlier removal(SOR)method is used to remove noise from the original airborne LiDAR point cloud data.Secondly,utilizing the slope and elevation threshold of regular grids,the slope filtering method of ground points is designed for tidal flat point cloud data.Lastly,actual airborne LiDAR point cloud of the tidal flat in Changsha portof Rudong city is selected as experimental data to carry out the construction of tidal flat DEM and its accuracy is test,so as to verify the proposed method of point cloud filtering.Experimental results show that the accuracy of DEM constructed by LiDAR point cloud by the proposed methodmeets could meet the requirements of national and industrial standards.