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EN
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.
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