Applicability analysis of cloth simulation filtering algorithm for mobile LiDAR point cloud

作者：Cai Shangshu; Zhang Wuming^*; Qi Jianbo; Wan Peng; Shao Jie; Shen Aojie

来源：2018 ISPRS TC III Mid-Term Symposium on Developments, Technologies and Applications in Remote Sensing, 2018-05-07 To 2018-05-10.

DOI：10.5194/isprs-archives-XLII-3-107-2018

• Applicability analysis
• Cloth simulation
• Distribution features
• Ground point
• Laser scanning
• LIDAR (light detection and ranging)
• Lidar point clouds
• Three-dimensional data

Classifying the original point clouds into ground and non-ground points is a key step in lidar (light detection and ranging) data post-processing. cloth simulation filtering (CSF) algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS) has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM), 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature) for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44%, 0.77% and 1.20%. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

• 出版日期2018
• 单位遥感科学国家重点实验室