Scopus
YÖKSİS ISSN Eşleşti
SJR Q1
An approach for the automated extraction of road surface distress from a UAV-derived point cloud
Automation in Construction · Şubat 2021
YÖKSİS Kayıtları — ISSN Eşleşmesi
An approach for the automated extraction of road surface distress from a UAV-derived point cloud
2021 ISSN: 0926-5805 SCI-Expanded Q1
Doç. Dr. MUSTAFA ZEYBEK →
Makale Bilgileri
ISSN09265805
Yayın TarihiŞubat 2021
Cilt / Sayfa122
Scopus ID2-s2.0-85096878369
Özet
The condition of the road surface should be inspected to increase the service life of the road and to ensure safety and comfort. This study aims to automatically detect and measure road distress from unmanned aerial vehicle (UAV)-based images. The proposed methodology consists of three steps. First, images acquired from the UAV are used to generate the three-dimensional point cloud. Then, the road surface is extracted from the 3D point cloud. Finally, the developed algorithm is used to automatically detect and measure road distress. The accuracy assessment is conducted by comparing the analyses from point cloud data and measurements obtained from the traditional inspection method. The root mean square error values range from 2.09–6.72 cm. Finally, the outcomes of the proposed methodology are compared with those of commercial GIS software. Both produce statistically similar results for detecting road surface distress.
Yazarlar (2)
1
Serkan Biçici
ORCID: 0000-0002-0621-9324
2
Mustafa Zeybek
ORCID: 0000-0001-8640-1443
Anahtar Kelimeler
Point cloud
Road distress detection
Road measurement
Road monitoring
UAV
Kurumlar
Artvin Coruh University, Turkey
Artvin Turkey
Scimago Dergi (ISSN Eşleşmesi)
Automation in Construction
Q1
SJR Skoru2,890
H-Index200
YayıncıElsevier B.V.
ÜlkeNetherlands
Building and Construction (Q1)
Civil and Structural Engineering (Q1)
Control and Systems Engineering (Q1)
Metrikler
78
Atıf
2
Yazar
5
Anahtar Kelime