Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/1620
Title: Point cloud filtering on UAV based point cloud
Authors: Zeybek, Mustafa
Şanlıoğlu, İsmail
Keywords: UAV
Point cloud
Filtering
Bare earth
Extraction
FROM-MOTION PHOTOGRAMMETRY; AIRBORNE LIDAR DATA; UNMANNED AERIAL VEHICLE; DIGITAL ELEVATION MODEL; MORPHOLOGICAL FILTER; ACCURACY; ALGORITHMS; GENERATION; ENVIRONMENTS; PERFORMANCE
Issue Date: 2019
Publisher: ELSEVIER SCI LTD
Abstract: Nowadays, Unmanned Aerial Vehicles (UAVs) have been attracted wide attentions such as a new measurement equipment and mapping, which are capable of the high-resolution point cloud data collection. In addition, a massive point cloud data has brought about the data filtering and irregular data organization for the generation of digital terrain models. Filtering of point clouds contains vegetations and artificial objects play a crucial role for bare earth terrain modelling. Topographical maps rely on the data structures which are built on bare ground terrain points. The bare earth surface extraction is not the only crucial to the topographical maps but also decision-making processes such as natural hazards management, deformation analysis and interpretation. In order to filter a UAV-based 3D raw point cloud data, in this paper, filtering performance of four different algorithms using open source and commercial software's have been investigated, (1) curvature based (Multiscale Curvature Classification-MCC), (2) surface-based filtering (FUSION), (3) progressive TIN based (LasTool-LasGround module-commercial) and (4) physical simulation processing (Cloth Simulation Filtering-CSF). The applied filtering results were validated with the reference data set classified by operator. Although different filtering methodologies implemented on point clouds, these methods demonstrated similar results to extract ground on distinctive terrain feature such as dense vegetated, flat surface, rough and complex landscapes. The filtering algorithms' results revealed that UAV-generated data suitable for extraction of bare earth surface feature on the different type of a terrain. Accuracy of the filtered point cloud reached the 93% true classification on flat surfaces from CSF filtering method. (C) 2018 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.measurement.2018.10.013
https://hdl.handle.net/20.500.13091/1620
ISSN: 0263-2241
1873-412X
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

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