Filtering airborne LiDAR data based on multi-view window and multi-resolution hierarchical cloth simulation

被引:1
作者
Cai, Shangshu [1 ,2 ,3 ]
Pang, Yong [1 ,2 ]
Yu, Sisi [4 ,5 ,6 ]
Lin, Xiangguo [7 ]
Liang, Xinlian [3 ]
机构
[1] Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing, Peoples R China
[2] Natl Forestry & Grassland Adm, Key Lab Forestry Remote Sensing & Informat Syst, Beijing, Peoples R China
[3] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan, Peoples R China
[4] Chinese Acad Forestry, Ecol & Nat Conservat Inst, Beijing, Peoples R China
[5] Chinese Acad Forestry, Res Inst Protected Area, Beijing, Peoples R China
[6] Key Lab Biodivers Conservat Natl Forestry & Grassl, Beijing, Peoples R China
[7] Chinese Acad Surveying & Mapping, Inst Photogrammetry & Remote Sensing, Beijing, Peoples R China
来源
GEO-SPATIAL INFORMATION SCIENCE | 2024年
基金
国家重点研发计划;
关键词
Light Detection and Ranging (LiDAR); ground filtering; multi-view window; cloth simulation; POINT CLOUDS; ALGORITHMS; SEGMENTATION;
D O I
10.1080/10095020.2024.2354211
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Ground filtering is a fundamental step in airborne LiDAR data processing toward a variety of applications. However, existing algorithms remain tremendously challenging in complex environments, e.g. steep hillsides, ridges, valleys, discontinuities, and numerous objects. We presented a new ground filtering algorithm that can handle various landscapes. First, the multi-view window is developed to increase the number of ground seeds on the various terrains. Second, multi-resolution hierarchical cloth simulation is used to rapidly construct the high-resolution reference terrain, and bidirectional internal force operation is proposed to improve the accuracy of reference terrain by smoothing the spikes in cloth. Finally, ground and non-ground points are classified based on the height differences between points and the reference terrain. The proposed algorithm was validated not only in the International Society for Photogrammetry and Remote Sensing (ISPRS) but also karst datasets, where particularly complex environments is contained. Results showed that the proposed algorithm outperformed the existing algorithms, with the lowest average total error of 3.85% and the highest average kappa coefficient of 87.75%. Moreover, the proposed algorithm can completely preserve complex terrain, e.g. extremely steep hillsides, and sharp ridges. This study had great potential to provide a useful tool for LiDAR data processing.
引用
收藏
页数:18
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