Enhancing Long-Term Bridge Performance Through the Use of Remote Sensing

Adriana C. Trias-Blanco, Sharef Farrag, Jie Gong, Franklin L. Moon

Research output: Contribution to journalConference articlepeer-review


An uprising use of LiDAR in bridge engineering is focused on condition assessment. Researchers are focused on investigating how the use of diverse remote sensing technologies individually and collectively can enhance the data gathered throughout the transportation infrastructure, tackling surface damage detection and quantification, crack detection, and estimation of corrosion areas on structural members. This research aims to evaluate the ability of LiDAR to contribute to improved bridge assessment and management, through the performance of LiDAR scanning during and after the construction of a bridge deck to: (a) evaluate the ability of providing real-time verification of design specifications, and (b) to capture detailed surface deck profile information that allows examining correlations to non-destructive evaluations (NDE) technologies results (Ground Penetrating Radar (GPR) and Half Cell Potential (HCP)). After analyzing the results obtained through LiDAR, it can be concluded that the bridge deck profile can be captured and defined within an accuracy of ± 2 mm on a 10 to 25 m range. Additionally, if the profile of the top and bottom of the deck are able to be captured before and after construction it is possible to estimate the top rebar cover that can be used to predict possible initial deterioration locations. Moreover, when comparing the estimated deck profile and geometry with the NDE data, it was possible to determine that areas where the slope was between -0.5% and 0.5% presented higher values for potential corrosion, and areas where the top rebar cover was below 1.5 in. presented a higher vulnerability for corrosion. Finally, it is recommended to perform LiDAR scanning during and after construction inspections of bridge decks to add valuable information to the Long-Term Bridge Performance suite of NDE technologies.

Original languageEnglish (US)
Pages (from-to)1149-1153
Number of pages5
JournalInternational Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII
StatePublished - 2021
Externally publishedYes
Event10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2021 - Porto, Portugal
Duration: Jun 30 2021Jul 2 2021

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Civil and Structural Engineering
  • Building and Construction


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