Assessment of the Accuracy of Terrestrial Laser Scanners in Detecting Local Surface Anomaly

Algadhi, Ali; Psimoulis, Panos; Grizi, Athina; Neves, Luis

Abstract

The surface anomaly is a common defect for structures that resist lateral stresses, such as retaining walls. The accurate detection of an anomaly using contactless techniques, such as the Terrestrial Laser Scanner (TLS), is significant for the reliable structural assessment. The influence of the scanning geometry on the accuracy of the TLS point-clouds was investigated in previous studies; however, a deeper analysis is needed to investigate their impact in the context of structural health monitoring. This paper aims to empirically assess the performance of the TLS in detecting surface anomalies, with respect to the scanning distance and angle of incidence in two cases: (i) when both the reference and deformed clouds are taken from the same scanning position, and (ii) the scans are from different positions. Furthermore, the paper examines the accuracy of estimating the depth of the anomaly using three cloud comparison techniques (i.e., C2C, C2M, and M3C2 methods). The results show that the TLS is capable of detecting the surface anomaly for distances between 2 and 30 m and angles of incidence between 90° and 30°, with a tolerance of within a few millimeters. This is achieved even for the case where scans from different locations (i.e., angles and distances) are applied.

Citation

Algadhi, A., Psimoulis, P., Grizi, A., & Neves, L. (2024). Assessment of the Accuracy of Terrestrial Laser Scanners in Detecting Local Surface Anomaly. Remote Sensing, 16(24), Article 4647. https://doi.org/10.3390/rs16244647

• Journal Article Type: Article
• Acceptance Date: Dec 9, 2024
• Online Publication Date: Dec 11, 2024
• Publication Date: 2024-12
• Deposit Date: Dec 12, 2024
• Publicly Available Date: Dec 12, 2024
• Journal: Remote Sensing
• Electronic ISSN: 2072-4292
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 24
• Article Number: 4647
• DOI: https://doi.org/10.3390/rs16244647
• Keywords: TLS; SHM; surface anomaly; change detection; C2C; C2M; M3C2; LiDAR
• Public URL: https://nottingham-repository.worktribe.com/output/42837070
• Publisher URL: https://www.mdpi.com/2072-4292/16/24/4647