An approach for the automated extraction of road surface distress from a UAV-derived point cloud

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dc.authorid0000-0002-0621-9324en_US
dc.authorid0000-0001-8640-1443en_US
dc.contributor.authorBiçici, Serkan
dc.contributor.authorZeybek, Mustafa
dc.date.accessioned2020-12-28T07:05:25Z
dc.date.available2020-12-28T07:05:25Z
dc.date.issued2021
dc.departmentAÇÜ, Mühendislik Fakültesien_US
dc.description.abstractThe 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.
dc.description.sponsorshipThis work was supported by the Artvin Coruh University Scientific Research Projects Coordinatorship (Grant No. 2019.F40.02.02 )en_US
dc.identifier.citationBiçici, S., & Zeybek, M. (2021). An approach for the automated extraction of road surface distress from a UAV-derived point cloud. Automation in Construction, 122, 103475.en_US
dc.identifier.doi10.1016/j.autcon.2020.103475
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.autcon.2020.103475
dc.identifier.urihttps://hdl.handle.net/11494/2500
dc.identifier.volume122en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorZeybek, Mustafa
dc.institutionauthorBiçici, Serkan
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.relation.ispartofAutomation in Construction
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectUAVen_US
dc.subjectPoint clouden_US
dc.subjectRoad distress detectionen_US
dc.subjectRoad measurementen_US
dc.subjectRoad monitoringen_US
dc.titleAn approach for the automated extraction of road surface distress from a UAV-derived point clouden_US
dc.typeArticle

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