Year: 2021
Type: article
Abstract: Point cloud filtering is an important step in Digital Terrain Model (DTM) production.Despite the fact that a great body of research has been conducted in this area so far, there are still some problems that have not yet been solved, especially in complex terrains.The fact that the use of user-defined parameters within the presented point cloud filtering methods, and the difficulty of parameter estimation in parallel to the increase in the topography slope and above-ground object diversity, decreases the filtering success.Another problem is the proper specification of the point cloud density to be studied.Point cloud density, which is generally specified considering the ground sampling distance of the DTM, influences the success of the point cloud filtering process, therefore, the accuracy of the DTM produced.In this study, five Unmanned Aerial System (UAS)-based point clouds of different densities were filtered using two different point cloud filtering algorithms Cloth Simulation Filtering (CSF) and gLiDAR to examine the impacts of the point cloud density on filtering success.It was found that the point cloud filtering performance decreased as the point density increased.
Authors: Çiğdem ŞERİFOĞLU YILMAZ, Oguz GÜNGÖR
Institutions: Karadeniz Technical University, Ankara University
Language: English
Subfield: Forestry
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W3137445296