Infrastructure evaluation is currently performed through visual inspection by experienced and trained inspection
personnel. Unmanned aerial vehicles (UAVs) have the potential to permanently transform infrastructure assessment.
UAVs can access difficult to reach areas and collect high resolution images and carry different sensing modalities.
Researchers at Drexel University are exploring the potential of UAVs for infrastructure assessment. Among the tests
conducted, a portable infrared thermography (IRT) was performed to map a mock up bridge deck for the
identification of subsurface delamination. High resolution images were also taken to plot the visual image of the
whole deck for surface crack identification. Another test using a manned helicopter performed an inspection of a
long span bridge using multispectral images. These multispectral aerial images were collected using both infrared
(IR) and RGB camera during scanning the bridge superstructure. Global views of the bridge using both sets of
images were created with an image stitching algorithm. The global views are qualitative, but with enhanced
algorithms leveraging GPS data, the technique will allow to locate damage in infrastructure, such as deterioration in
bridge decks.
1. Hilton, M.H., Application of close-range terrestrial photogrammetry to bridge structures. Final report.
1985.
2. Li, J.-C. and B.-Z. Yuan. Using vision technique for the bridge deformation detection. in Acoustics, Speech,
and Signal Processing, 1988. ICASSP-88., 1988 International Conference on. 1988. IEEE.
3. Li, W., G. Li, and T. Xu. Determination of the deformation of the bridge model in real time with CCD solid
state camera. in Close-Range Photogrammetry Meets Machine Vision. 1990.
4. Forno, C., et al., The measurement of deformation of a bridge by Moirè photography and photogrammetry.
Strain, 1991. 27(3): p. 83-87.
5. Al-Turk, E. and W. Uddin, Infrastructure inventory and condition assessment using airborne laser terrain
mapping and digital photography. Transportation Research Record: Journal of the Transportation Research
Board, 1999. 1690(1): p. 121-125.
6. aillard and a tre 3-D Reconstruction of Urban Scenes from Aerial Stereo Imagery: A Focusing
Strategy. Computer Vision and Image Understanding, 1999. 76(3): p. 244-258.
7. Cord, M., M. Jordan, and J.-P. Cocquerez, Accurate Building Structure Recovery from High Resolution
Aerial Imagery. Computer Vision and Image Understanding, 2001. 82(2): p. 138-173.
130
8. Mitomi, H., et al. Automated damage detection of buildings from aerial television images of the 2001
Gujarat, India earthquake. in Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001
International. 2001.
9. Jáuregui, D.V., et al., Noncontact photogrammetric measurement of vertical bridge deflection. Journal of
Bridge Engineering, 2003. 8(4): p. 212-222.
10. Lee, J.J. and M. Shinozuka, A vision-based system for remote sensing of bridge displacement. Ndt & E
International, 2006. 39(5): p. 425-431.
11. Zhengrong, L., et al. Knowledge-based power line detection for UAV surveillance and inspection systems.
in Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference. 2008.
12. Liu, W., S.-E. Chen, and E. Hauser. Remote sensing for bridge health monitoring. in Atmospheric and
Environmental Remote Sensing Data Processing and Utilization V: Readiness for GEOSS III, August 5,
2009 - August 6, 2009. 2009. San Diego, CA, United states: SPIE.
13. Chen, S.-E., et al. Small-format fly-over photography for highway bridge monitoring. in Sensors and Smart
Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, March 8, 2010 - March 11,
2010. 2010. San Diego, CA, United states: SPIE.
14. Rosenbaum, D., et al., Real-time image processing for road traffic data extraction from aerial images.
2010: na.
15. Adams, S.M. and C.J. Friedland. A survey of unmanned aerial vehicle (UAV) usage for imagery collection
in disaster research and management. in 9th International Workshop on Remote Sensing for Disaster
Response. 2011.
16. Bian, H., et al. Bridge deck joints evaluation using lidar and aerial photography. 2011.
17. Chen, S.-E., et al., Small-format aerial photography for highway-bridge monitoring. Journal of
Performance of Constructed Facilities, 2011. 25(2): p. 105-112.
18. Vaghefi, K., et al., Evaluation of commercially available remote sensors for highway bridge condition
assessment. Journal of Bridge Engineering, 2011. 17(6): p. 886-895.
19. Daniel Cusson, et al., Remote Monitoring of Bridges From Space, in Proceedings of the 54th Brazilian
Congress of concrete. 2012: Brazil.
20. Natarajan, M., et al. Issues in bridge deck damage evaluation using aerial photos. in SPIE Smart Structures
and Materials+ Nondestructive Evaluation and Health Monitoring. 2012. International Society for Optics
and Photonics.
21. Avendano, J., L.D. Otero, and P. Cosentino. Towards the development of a complex structural inspection
system using small-scale aerial vehicles and image processing. 2013. Piscataway, NJ, USA: IEEE.
22. Fuad Khan, et al., Multi-sensing NDT for damage assessment of concrete masonry walls. Structural Control
and Health Monitoring, 2014.
23. Khan, F., et al. Acoustics and temperature based NDT for damage assessment of concrete masonry system
subjected to cyclic loading. 2014.
24. Pla-Rucki, G.F. and M.O. Eberhard, Imaging of reinforced concrete: State-of-the-art review. Journal of
Infrastructure Systems, 1995. 1(2): p. 134-141.
25. Büyüköztürk, O., Imaging of concrete structures. Ndt & E International, 1998. 31(4): p. 233-243.
26. Clark, M., D. McCann, and M. Forde, Application of infrared thermography to the non-destructive testing
of concrete and masonry bridges. Ndt & E International, 2003. 36(4): p. 265-275.
27. Hing, C.C. and U.B. Halabe, Nondestructive testing of GFRP bridge decks using ground penetrating radar
and infrared thermography. Journal of Bridge Engineering, 2010. 15(4): p. 391-398.
28. Washer, G., R. Fenwick, and N. Bolleni, Effects of solar loading on infrared imaging of subsurface
features in concrete. Journal of Bridge Engineering, 2010. 15(4): p. 384-390.
29. Vaghefi, K., H.A.d.M. e Silva, and D.K. Harris, Application of thermal ir imagery for concrete bridge
inspection. 2011.
30. Oh, T., et al., Comparison of NDT methods for assessment of a concrete bridge deck. Journal of
Engineering Mechanics, 2012. 139(3): p. 305-314.
31. Washer, G., et al., Guidelines for Thermographic Inspection of Concrete Bridge Components in Shaded
Conditions. Transportation Research Record: Journal of the Transportation Research Board, 2013. 2360(1):
p. 13-20.
32. Matsumoto, M., K. Mitani, and F.N. Catbas. Non-Destructive Bridge Deck Assessment using Image
Processing and Infrared Thermography. in Transportation Research Board 93rd Annual Meeting. 2014.