Scopus
YÖKSİS Eşleşti
Point cloud filtering on UAV based point cloud
Measurement: Journal of the International Measurement Confederation · Şubat 2019
YÖKSİS Kayıtları
Point cloud filtering on UAV based point cloud
Measurement · 2019 SCI-Expanded
DOÇENT MUSTAFA ZEYBEK →
Makale Bilgileri
DergiMeasurement: Journal of the International Measurement Confederation
Yayın TarihiŞubat 2019
Cilt / Sayfa133 · 99-111
Scopus ID2-s2.0-85054426341
Özet
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.
Yazarlar (2)
1
Mustafa Zeybek
ORCID: 0000-0001-8640-1443
2
İsmail Şanlıoğlu
ORCID: 0000-0002-3093-335X
Anahtar Kelimeler
Bare earth
Extraction
Filtering
Point cloud
UAV
Kurumlar
Artvin Coruh University, Turkey
Artvin Turkey
Konya Technical University
Konya Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
114
Atıf
2
Yazar
5
Anahtar Kelime