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Pavements require regular maintenance due to the wear and tear caused by traffic loads and environmental conditions, which lead to various surface defects. This study explores the use of Light Detection and Ranging (LiDAR) technology and ArcGIS software to identify pavement defects in selected regions of Malaysia. The Jambatan Sultan Abdul Halim Muadzam Shah Expressway (JSAHMSE) and the Guthrie Corridor Expressway (GCE) were chosen as test sites for evaluating this approach. Initially, point cloud data were collected from both expressways using LiDAR, and related images were processed through ArcGIS software to identify defects on the road surfaces. The analysis revealed defects such as shoving, bleeding, longitudinal cracking, potholes, and patching on the GCE, while raveling, longitudinal cracking, bleeding, and edge cracking were observed on the JSAHMSE. Simultaneously, manual visual inspections were conducted, and defects were documented. A comparison of the results from both methods showed that LiDAR and ArcGIS effectively identified the types and sizes (length and surface area) of the defects. However, ArcGIS struggled to accurately measure the depth of certain defects, making it difficult to assess their severity in detail.
Rocznik
Tom
Strony
73--85
Opis fizyczny
Bibliogr. 28 poz.
Twórcy
autor
- Department of Civil Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
- School of Housing, Building and Planning, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
autor
- School of Housing, Building and Planning, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
autor
- School of Housing, Building and Planning, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
Bibliografia
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- 21. Yang Mengmeng, Youchuan Wan, Xianlin Liu, Jingzhong Xu, Zhanying Wei, Maolin Chen, Peng Sheng. 2018. "Laser data based automatic recognition and maintenance of road markings from MLS system."Optics & Laser Technology 107: 192-203. ISSN: 00303992. DOI: https://doi.org/10.1016/j.optlastec.2018.05.027.
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- 26. Jung Jaehoon, Erzhuo Che, Michael J. Olsen, Christopher Parrish. 2019. "Efficient and robust lane marking extraction from mobile lidar point clouds." ISPRS journal of photogrammetry and remote sensing 147: 1-18. ISSN: 0924-2716. DOI: https://doi.org/10.1016/j.isprsjprs.2018.11.012.
- 27.Martín-Jiménez José Antonio, Santiago Zazo, José Juan Arranz Justel, Pablo Rodríguez-Gonzálvez, Diego González-Aguilera. 2018. "Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree." ISPRS journal of photogrammetry and remote sensing 146: 334-346. DOI: https://doi.org/10.1016/j.isprsjprs.2018.10.004.
- 28. Holgado-Barco Alberto, Diego Gonzalez-Aguilera, Pedro Arias-Sanchez, Joaquín Martinez-Sanchez. 2014. "An automated approach to vertical road characterisation using mobile LiDAR systems: Longitudinal profiles and cross-sections." ISPRS Journal of Photogrammetry and Remote Sensing 96: 28-37. ISSN: 0924-2716. DOI: https://doi.org/10.1016/j.isprsjprs.2014.06.017.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e89d7058-8b95-4a75-b8eb-7f7130b16fec
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