基于无人机LiDAR点云的多类型植被覆盖滩涂地形滤波

滩涂是宝贵的自然资源，其地形的高精度反演具有重要科学价值，而现有技术和方法存在较大的局限性。无人机激光雷达技术可快速获取大范围滩涂高精度、高密度的三维点云数据，是滩涂地形反演的重要技术之一。如何对点云数据中滩涂植被进行高精度滤波是地形反演要解决的技术难点，尤其是当滩涂覆盖有茂密的异质性植被（如不同种类和几何形态）时，对滤波算法的通用性和鲁棒性提出了更高的要求。以上海崇明西滩湿地某一滩涂作为研究区域，选取草丛、灌木和高大乔木3类典型植被覆盖的局部区域，利用基于坡度滤波、渐进数学形态学滤波和布料模拟滤波3种常用的点云滤波算法进行点云数据处理，比较分析了3种方法的适用性。结果表明：布料模拟滤波对于3个典型区域实验结果的总误差分别为1.57%、0.16%和0.23%， Kappa系数分别为96.74%、98.70%和99.30%。相较于其他两种算法，布料模拟滤波精度更高，更适用于多类型植被覆盖滩涂区域。因此，采用布料模拟滤波对整个研究区域进行处理，取得了较好的滤波效果，与真实地面吻合度较高。最后，通过克里金插值得到整个研究区域高精度的地形数据。

Multi-type Vegetation Coverage Tidal Flat Terrain Filtering based on UAV LiDAR Point Cloud

Tidal flats are precious natural resources， and the high-precision inversion of the topography has important scientific value. However， the existing technologies and methods have great limitations. UAV LiDAR technology can quickly obtain high-precision and high-density three-dimensional point cloud data of large-area tidal flats， which is one of the important technologies for tidal flat terrain inversion. How to perform high-precision filtering of the tidal flat vegetation in the point cloud data is a technical difficulty to be solved in terrain inversion. Particularly， the universality and robustness of the filtering algorithm should be considered when the tidal flat is covered with dense heterogeneous vegetation （e.g.， different types and geometric forms）. In this paper， a tidal flat of Chongming Xitan in Shanghai is selected as the research area. Three typical vegetation coverage areas （grass， shrub and tall tree）， are selected. Three typical point cloud filtering algorithms （slope filtering， progressive mathematical morphology filtering， and cloth simulation filtering） are used to process the point cloud data， and the results are compared to analyze the applicability of the three methods. The results show that the total error of cloth simulation filtering for the three typical areas is 1.57%， 0.16% and 0.23% respectively， and the kappa coefficient is 96.74%， 98.70% and 99.30% respectively. Compared with the other two algorithms， the accuracy of the cloth simulation filtering is higher， and it is more suitable for multi-type vegetation covering tidal flat areas. Therefore， the cloth simulation filtering is used to process the entire study area. A satisfactory filtering result is obtained， which is in good agreement with the real topography. Finally， the high-precision topographic data of the entire study area is obtained through kriging interpolation.