A slope filtering method for point cloud of dense vegetation terrain based on airborne LiDAR

Jinqi Chen; Chuanli Kang; Siyao Zhang; Yiling Lan; Jiale Yang

doi:10.1117/12.2682654

1 June 2023 A slope filtering method for point cloud of dense vegetation terrain based on airborne LiDAR

Jinqi Chen, Chuanli Kang, Siyao Zhang, Yiling Lan, Jiale Yang

Proceedings Volume 12710, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2023); 127100D (2023) https://doi.org/10.1117/12.2682654
Event: International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2023), 2023, Changsha, China

Abstract

In order to obtain the real ground point cloud, it is necessary to filter the original point cloud data to remove the non ground points. In the subtropical evergreen broad-leaved forest belt, the vegetation is dense, and the ground points are seriously sheltered. The ground points and non ground points are staggered. According to the characteristics of point clouds in the natural belt of the study area, this paper proposes a slope filtering method for dense vegetation terrain point clouds of airborne LiDAR. First, the virtual grid is introduced to segment the point cloud data, and the grid index of each point is calculated; Then calculate the elevation of the lowest point in each grid to calculate the height difference between each point and the lowest point in each grid. Then, the slope values of all points in each grid are obtained, and the local slope statistics are carried out to calculate the slope threshold; Finally, ground point filtering is carried out according to the adaptive slope threshold obtained by preset height difference threshold, k-means clustering and normal distribution. The flat terrain area and undulating terrain area are used for experimental analysis respectively. The results show that this method solves the problem of dense filtering of non surface points, and can not only remove dense vegetation but also retain terrain details.

Citation Download Citation

Jinqi Chen, Chuanli Kang, Siyao Zhang, Yiling Lan, and Jiale Yang "A slope filtering method for point cloud of dense vegetation terrain based on airborne LiDAR", Proc. SPIE 12710, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2023), 127100D (1 June 2023); https://doi.org/10.1117/12.2682654

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KEYWORDS

Tunable filters

Point clouds

Vegetation

Image filtering

LIDAR

Statistical analysis

Digital filtering

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