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J. Compos. Sci.
Volume 9
Issue 12
10.3390/jcs9120665
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Defect Visualization in the Bridge Underpass Arch Structure: A Photogrammetry Assessment Using UAV-Captured Imagery

by
Muhammad Ali Musarat
1,2,*,
Carl James Debono
1,*,
Vijay Prakash
1,
Ruben Paul Borg
2,
Dylan Seychell
3,
Gabriel Hili
3,
Jiangpeng Shu
4 and
Wei Ding
4
1
Department of Communications and Computer Engineering, Faculty of ICT, University of Malta, MSD2080 Msida, Malta
2
Faculty for the Built Environment, University of Malta, 2080 Msida, Malta
3
Department of Artificial Intelligence, Faculty of ICT, University of Malta, MSD2080 Msida, Malta
4
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
*
Authors to whom correspondence should be addressed.
J. Compos. Sci. 2025, 9(12), 665; https://doi.org/10.3390/jcs9120665 (registering DOI)
Submission received: 2 October 2025 / Revised: 12 November 2025 / Accepted: 21 November 2025 / Published: 2 December 2025
(This article belongs to the Special Issue Structural Design, Health Monitoring and Performance Evaluation of Composite Materials)
Versions Notes

Abstract

Concrete structures develop several defects as the structure ages. One of the common concerns in structural integrity is the formation of cracks, which demands regular inspection with precision. In this study, a bridge underpass arch structure was inspected with the help of an Unmanned Aerial Vehicle (UAV) in a coastal region of the Mediterranean Sea, where 2D captured images were transferred into a 3D model for better visualisation from a Structural Health Monitoring (SHM) perspective. The images with cracks were manually annotated, using the VGG tool, by an expert. Using the 3DF Zephyr software, from sparse to dense point clouds, and 3D mesh to orthophoto, all 3D models were constructed from the annotated and unannotated images of the structure. The 3D model achieved a Ground Sampling Distance of 0.0046 m/pixel, with an image alignment of 60%. The Bundle Adjustment Mean Reprojection Error confirmed satisfactory internal model accuracy. The final assessment through the orthophoto, where a resolution of 4531 × 2433 pixels was achieved, revealed that the images were of sufficient quality to capture the details and the defects present, and better visualisation could be made. This output demonstrates that UAV-based photogrammetry is time- and cost-efficient and surpasses the traditional visual inspection of confined structures.
Keywords: UAV; SHM; 3D model; infrastructure assessment; visualisation UAV; SHM; 3D model; infrastructure assessment; visualisation

Share and Cite

MDPI and ACS Style

Musarat, M.A.; Debono, C.J.; Prakash, V.; Borg, R.P.; Seychell, D.; Hili, G.; Shu, J.; Ding, W. Defect Visualization in the Bridge Underpass Arch Structure: A Photogrammetry Assessment Using UAV-Captured Imagery. J. Compos. Sci. 2025, 9, 665. https://doi.org/10.3390/jcs9120665

AMA Style

Musarat MA, Debono CJ, Prakash V, Borg RP, Seychell D, Hili G, Shu J, Ding W. Defect Visualization in the Bridge Underpass Arch Structure: A Photogrammetry Assessment Using UAV-Captured Imagery. Journal of Composites Science. 2025; 9(12):665. https://doi.org/10.3390/jcs9120665

Chicago/Turabian Style

Musarat, Muhammad Ali, Carl James Debono, Vijay Prakash, Ruben Paul Borg, Dylan Seychell, Gabriel Hili, Jiangpeng Shu, and Wei Ding. 2025. "Defect Visualization in the Bridge Underpass Arch Structure: A Photogrammetry Assessment Using UAV-Captured Imagery" Journal of Composites Science 9, no. 12: 665. https://doi.org/10.3390/jcs9120665

APA Style

Musarat, M. A., Debono, C. J., Prakash, V., Borg, R. P., Seychell, D., Hili, G., Shu, J., & Ding, W. (2025). Defect Visualization in the Bridge Underpass Arch Structure: A Photogrammetry Assessment Using UAV-Captured Imagery. Journal of Composites Science, 9(12), 665. https://doi.org/10.3390/jcs9120665

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