Paper Info
Title
Sensitivity Analysis Of Parameters And Contrasting Performance Of Ground Filtering Algorithms With Uav Photogrammetry-Based And Lidar Point Clouds
Abstract
Most ground filtering algorithms are primarily designed for airborne LiDAR point cloud processing and their successful use in identifying ground points from photogrammetric point clouds remains questionable. We compared six ground filtering algorithms implemented in Metashape, ArcGIS, CloudCompare, LAStools, and PDAL. We used UAV photogrammetry-based (acquired under leaf-off conditions) and airborne LiDAR (leaf-on) point clouds of the same area to: (i) compare accuracy of generated DTMs; (ii) evaluate the effect of vegetation density and terrain slope on filtering accuracy; and (iii) assess which algorithm parameters have the greatest effect on the filtering accuracy. Our results show that the performance of filtering algorithms was affected by the point cloud type, terrain slope and vegetation cover. The results were generally better for LiDAR (RMSE 0.13-0.19 m) than for photogrammetric (RMSE 0.19-0.23 m) point clouds. The behavior in varying vegetation and terrain conditions was consistent for LiDAR point clouds. However, when applied on photogrammetric point clouds, the algorithms' behavior was inconsistent, especially in areas of steep slope (except for the Progressive Triangulated Irregular Network in LAStools). Parameters related to the selection of the initial minimum elevation ground points were the most influential in all algorithms and point clouds.
Year
DOI
Venue
2020
10.1080/17538947.2020.1791267
INTERNATIONAL JOURNAL OF DIGITAL EARTH
Keywords
DocType
Volume
DTM, filtering, LiDAR, point cloud, spoil heap, UAV
Journal
13
Issue
ISSN
Citations 
12
1753-8947
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Petr Klápště100.34
Michal Fogl200.34
Vojtěch Barták300.34
Kateřina Gdulová400.34
Rudolf Urban500.34
Vítězslav Moudrý600.34