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Paper: lc3-2017-041
| Paper title: | A Case Study on Comparative Analysis of 3D Point Clouds from UAV and Terrestrial Scanners for Bridge Condition Assessment |
| Authors: | Varun Kasireddy and Burcu Akinci |
| Summary: | Recent improvements in 3D laser scanning technologies enabled accurate capturing of existing spatial conditions using point clouds. To leverage this progress for a more accurate condition assessment, state Department of Transportations (DOT) across the US have been utilizing scanning technologies through deployment of terrestrial laser scanners (TLS) and more recently Light Detection and Ranging (LIDAR) scanners fitted to UAVs. However, not much study thus far discusses the potential of these 3D point clouds captured from these two different data collection approaches for supporting automatic and detailed (element-level) condition assessment of bridges. The goal of this study is to compare the utilization of 3D point cloud generated from a terrestrial scanner with that from a UAV in supporting element-level condition assessment of bridges. This paper presents recent results from full scale deployment on a small/medium size highway bridge. An important component of our effort is to explore how well the collected data supports element level condition assessment as per National Bridge Inspection Standards (NBIS). This study assesses the potential to incorporate these data collection modalities into standard bridge safety inspection practice. |
| Type: | regular paper |
| Year of publication: | 2017 |
| Keywords: | Laser Scanning, Bridge, Condition Assessment, Element Level |
| Series: | jc3:2017 |
| Download paper: | /pdfs/LC3_2017_paper_041.pdf |
| Citation: | Varun Kasireddy and Burcu Akinci (2017). A Case Study on Comparative Analysis of 3D Point Clouds from UAV and Terrestrial Scanners for Bridge Condition Assessment. Lean and Computing in Construction Congress (LC3): Volume I Ð Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 87-94, http://itc.scix.net/paper/lc3-2017-041 |
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