Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study

Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a w...

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Autores principales:	Yi-Chun Lin, Jidong Liu, Yi-Ting Cheng, Seyyed Meghdad Hasheminasab, Timothy Wells, Darcy Bullock, Ayman Habib
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	bridge evaluation infrastructure inspection as-built data bridge deck thickness mobile LiDAR registration Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/3873447d8240469aaddec528a0c7281d
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spelling	oai:doaj.org-article:3873447d8240469aaddec528a0c7281d2021-11-25T18:57:22ZProcessing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study10.3390/s212275501424-8220https://doaj.org/article/3873447d8240469aaddec528a0c7281d2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7550https://doaj.org/toc/1424-8220Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a wide range of remote sensing technologies, among which mobile LiDAR is gaining increasing attention due to its ability to collect high-resolution data over a relatively large area in a short time. The quality of mobile LiDAR data depends not only on the grade of onboard LiDAR scanners but also on the accuracy of direct georeferencing information and system calibration. Consequently, millimeter-level accuracy is difficult to achieve. In this study, the performance of mapping-grade and surveying-grade mobile LiDAR systems for bridge monitoring is evaluated against static laser scanners. Field surveys were conducted over a concrete bridge where grinding was required to achieve desired smoothness. A semi-automated, feature-based fine registration strategy is proposed to compensate for the impact of georeferencing and system calibration errors on mobile LiDAR data. Bridge deck thickness is evaluated using surface segments to minimize the impact of inherent noise in the point cloud. The results show that the two grades of mobile LiDAR delivered thickness estimates that are in agreement with those derived from static laser scanning in the 1 cm range. The mobile LiDAR data acquisition took roughly five minutes without having a significant impact on traffic, while the static laser scanning required more than three hours.Yi-Chun LinJidong LiuYi-Ting ChengSeyyed Meghdad HasheminasabTimothy WellsDarcy BullockAyman HabibMDPI AGarticlebridge evaluationinfrastructure inspectionas-built databridge deck thicknessmobile LiDARregistrationChemical technologyTP1-1185ENSensors, Vol 21, Iss 7550, p 7550 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bridge evaluation infrastructure inspection as-built data bridge deck thickness mobile LiDAR registration Chemical technology TP1-1185
spellingShingle	bridge evaluation infrastructure inspection as-built data bridge deck thickness mobile LiDAR registration Chemical technology TP1-1185 Yi-Chun Lin Jidong Liu Yi-Ting Cheng Seyyed Meghdad Hasheminasab Timothy Wells Darcy Bullock Ayman Habib Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
description	Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a wide range of remote sensing technologies, among which mobile LiDAR is gaining increasing attention due to its ability to collect high-resolution data over a relatively large area in a short time. The quality of mobile LiDAR data depends not only on the grade of onboard LiDAR scanners but also on the accuracy of direct georeferencing information and system calibration. Consequently, millimeter-level accuracy is difficult to achieve. In this study, the performance of mapping-grade and surveying-grade mobile LiDAR systems for bridge monitoring is evaluated against static laser scanners. Field surveys were conducted over a concrete bridge where grinding was required to achieve desired smoothness. A semi-automated, feature-based fine registration strategy is proposed to compensate for the impact of georeferencing and system calibration errors on mobile LiDAR data. Bridge deck thickness is evaluated using surface segments to minimize the impact of inherent noise in the point cloud. The results show that the two grades of mobile LiDAR delivered thickness estimates that are in agreement with those derived from static laser scanning in the 1 cm range. The mobile LiDAR data acquisition took roughly five minutes without having a significant impact on traffic, while the static laser scanning required more than three hours.
format	article
author	Yi-Chun Lin Jidong Liu Yi-Ting Cheng Seyyed Meghdad Hasheminasab Timothy Wells Darcy Bullock Ayman Habib
author_facet	Yi-Chun Lin Jidong Liu Yi-Ting Cheng Seyyed Meghdad Hasheminasab Timothy Wells Darcy Bullock Ayman Habib
author_sort	Yi-Chun Lin
title	Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
title_short	Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
title_full	Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
title_fullStr	Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
title_full_unstemmed	Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
title_sort	processing strategy and comparative performance of different mobile lidar system grades for bridge monitoring: a case study
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3873447d8240469aaddec528a0c7281d
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_version_	1718410456540905472

Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study

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