Geometric feature extraction of road from UAV based point cloud data
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study presents a new approach to achieving the high accuracy geometric feature extraction of road surface automatically from UAV based images. The proposed methodology begins with the automatic extraction of road surface from point cloud. The extraction of road is based on point clouds and machine learning classification algorithm. Then, road boundaries are derived from extracted road surface points and are used to estimate the road centerline. The point clouds are then used to create digital elevation models to extract profile and cross-section elevations at specified intervals by referenced the estimated smooth road centerline. The accuracy of the road surface classification is evaluated by comparing manual classified points. According to the results, precise road extraction, road centerline, profile, and cross-sections are produced with high accuracy using the proposed approach.
Açıklama
This work was financed by the Artvin Coruh University Scientific Research Projects Coordinatorship (Grant No. 2019.F40.02.02). We want to acknowledge the Turkish General Directorate of Highways for supporting us to study on the road. The developed R codes can be downloadable from https://github.com/ mzeybek583/RRoad.git.
Anahtar Kelimeler
UAV, Road, Centerline, Profile, Cross-section
Kaynak
Lecture Notes in Networks and Systems/ 5th International Conference on Smart City Applications
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
183
Sayı
Künye
Zeybek, M., & Biçici, S. (2021).Geometric feature extraction of road from UAV based point cloud data. 5th International Conference on Smart City Applications, SCA 2020; Karabuk, Turkey; 7 October 2020 through 9 October 2020, 183, 435-449
