JDR Vol.13 No.2 pp. 281-290
doi: 10.20965/jdr.2018.p0281


Extraction of Collapsed Bridges Due to the 2011 Tohoku-Oki Earthquake from Post-Event SAR Images

Wen Liu and Fumio Yamazaki

Graduate School of Engineering, Chiba University
1-33 Yayoi-cho, Inageku, Chiba 263-8522, Japan

Corresponding author

November 15, 2017
January 22, 2018
Online released:
March 19, 2018
March 20, 2018
collapsed bridge, backscattering model, TerraSAR-X, GIS data, the 2011 Tohoku-oki earthquake

Since synthetic aperture radar (SAR) sensors onboard satellites can work under all weather and sunlight conditions, they are suitable for information gathering in emergency response after disasters occur. This study attempted to extract collapsed bridges in Iwate Prefecture, Japan, which was affected by more than 15-m high tsunamis due to the Mw 9.0 earthquake on March 11, 2011. First, the locations of the bridges were extracted using GIS data of roads and rivers. Then, we attempted to detect the collapsed or washed-away bridges using visual interpretation and thresholding methods. The threshold values on the SAR backscattering coefficients and the percentage of non-water regions were applied to the post-event high-resolution TerraSAR-X images. The results were compared with the optical images and damage investigation reports. The effective use of a single SAR intensity image in the extraction of collapsed bridges was demonstrated with a high overall accuracy of more than 90%.

Cite this article as:
W. Liu and F. Yamazaki, “Extraction of Collapsed Bridges Due to the 2011 Tohoku-Oki Earthquake from Post-Event SAR Images,” J. Disaster Res., Vol.13 No.2, pp. 281-290, 2018.
Data files:
  1. [1] National Institute for Land and Infrastructure Management (NILIM), “Annual report of road–related research in FY 2013,” Technical Note of NILIM, No.843, 2013, [in Japanese, available on Jan. 29, 2018]
  2. [2] G. Shoji and T. Nakamura, “Damage assessment of road bridges subjected to the 2011 Tohoku Pacific earthquake tsunami,” Journal of Disaster Research, Vol.12, No.1, pp. 79-89, doi: 10.20965/ jdr.2017.p0079, 2017.
  3. [3] K. Saito, R. J. S. Spence, C. Going, and M. Markus, “Using High-Resolution Satellite Images for Post-Earthquake Building Damage Assessment: A Study Following the 26 January 2001 Gujarat Earthquake,” Earthquake Spectra, Vol.20, No.1, pp. 145-169, 2004.
  4. [4] F. Yamazaki, Y. Yano, and M. Matsuoka, “Visual Damage Interpretation of Buildings in Bam City Using QuickBird Images Following the 2003 Bam, Iran, Earthquake,” Earthquake Spectra, Vol.21, No.S1, pp. 329-336, doi: 10.1193/1.1650865, 2005.
  5. [5] X. Tong, Z. Hong, S. Liu, X. Zhang, H. Xie, Z. Liu, S. Yang, W. Wange, and F. Bao, “Building-damage detection using pre- and post-seismic high-resolution satellite stereo imagery: A case study of the May 2008 Wenchuan earthquake,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol.68, pp. 13-27, doi: 10.1016/j.isprsjprs.2011.12.004, 2012.
  6. [6] L. Dong and J. Shan, “A comprehensive review of earthquake–induced building damage detection with remote sensing techniques,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol.84, pp. 85-99, doi: 10.1016/j.isprsjprs.2013.06.011, 2013.
  7. [7] P. T. B. Brett and R. Guida, “Earthquake damage detection in urban areas using curvilinear features,” IEEE Transactions on Geoscience and Remote Sensing, Vol.51, No.9, pp. 4877-4884, doi: 10.1016/j.isprsjprs.2013.06.011, 2013.
  8. [8] S. Plank, “Rapid damage assessment by means of multi-temporal SAR-A comprehensive review and outlook to Sentinel-1,” Remote Sensing, Vol.6, pp. 4870-4906, doi:10.3390/rs6064870, 2014.
  9. [9] D. Brunner, G. Lemoine, and L. Bruzzone, “Earthquake damage assessment of buildings using VHR optical and SAR imagery,” IEEE Transactions on Geoscience and Remote Sensing, Vol.48, No.5, pp. 2403-2420, doi: 10.1109/TGRS.2009.2038274, 2010.
  10. [10] W. Liu, F. Yamazaki, H. Gokon, and S. Koshimura, “Extraction of Tsunami Flooded Areas and Damaged Buildings in the 2011 Tohoku-oki, Japan Earthquake from TerraSAR-X Intensity Images,” Earthquake Spectra, Vol.29, No.S1, pp. S183-2000, doi: 10.1193/1.4000120, 2013.
  11. [11] H. Miura, S. Midorikawa, and M. Matsuoka, “Building damage assessment using high-resolution satellite SAR images of the 2010 Haiti earthquake,” EERI Earthquake Spectra, Vol.32, No.1, pp. 591-610, doi: 10.1193/033014EQS042M, 2016.
  12. [12] M. Wieland, W. Liu, and F. Yamazaki, “Learning change from Synthetic Aperture Radar images: Performance evaluation of a Support Vector Machine to detect earthquake and tsunami–induced changes,” Remote Sensing, Vol.8, issue 10, No.792, doi: 10.3390/rs8100792, 2016.
  13. [13] W. Liu, F. Yamazaki, B. Adriao, E. Mas, and S. Koshimura, “Development of building height data in Peru from high-resolution SAR imagery,” Journal of Disaster Research, Vol.9, No.6, pp. 1042-1049, doi: 10.20965/jdr.2014.p1042, 2014.
  14. [14] W. Liu, F. Yamazaki, and T. Sasagawa, “Monitoring of the recovery process of the Fukushima Daiichi nuclear power plant from VHR SAR images,” Journal of Disaster Research, Vol.11, No.2, pp. 236-245, doi: 10.20965/jdr.2016.p0236, 2016.
  15. [15] Y. Wang and Q. Zheng, “Recognition of roads and bridges in SAR images,” Pattern Recognition, Vol.31, No.7, pp. 953-962, doi: 10.1016/S0031-3203(97)00098-8, 1998.
  16. [16] U. Soergel, E. Cadario, A. Thiele, and U. Thoennessen, “Extraction of bridges over water in multi-aspect high-resolution InSAR data, International Archives of the Photogrammetry,” Proceedings of Symposium of ISPRS Commission III Photogrammetric Computer Vision PCV’06, Vol.XXXVI, part 3, 2006.
  17. [17] J. Luo, D. Ming, W. Liu, Z. Shen, M. Wang, and H. Sheng, “Extraction of bridges over water from IKONOS panchromatic data,” International Journal of Remote Sensing, Vol.28, issue 16, pp. 3633-3648, doi: 10.1080/01431160601024226, 2007.
  18. [18] U. Soergel, U. H. Gross, A. Thiele, and U. Thoennessen, “Feature extraction and visualization of bridges over water from high-resolution InSAR data and one orthophoto,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.1, No.2, pp. 147-153, doi: 10.1109/JSTARS.2008.2001156, 2008.
  19. [19] D. Chaudhuri and A. Samal, “An automatic bridge detection technique for multispectural images,” IEEE Transactions on Geoscience and Remote Sensing, Vol.46, issue 9, pp. 2720-2727, doi: 10.1109/TGRS.2008.923631, 2008.
  20. [20] M. Akiyama, D. M. Frangopol, M. Arai, and S. Koshimura, “Reliability of bridges under tsunami hazards: Emphasis on the 2011 Tohoku-oki earthquake,” Earthquake Spectra, Vol.29, No.S1. pp. S295-S314, doi: 10.1193/1.4000112, 2013.
  21. [21] G. Shoji and T. Nakamura, “Damage assessment of road bridges subjected to the 2011 Tohoku Pacific earthquake tsunami,” Journal of Disaster Research, Vol.12, No.1, pp. 79-89, doi: 10.20965/jdr.2017.p0079, 2017.
  22. [22] K. Inoue, W. Liu, and F. Yamazaki, “Detection of bridge damages due to Tsunami using multi-tempoeral high-resolution SAR images,” Journal of Japan Association for Earthquake Engineering, Vol.17, issue 5, pp. 48-59, doi: 10.5610/jaee.17.5_48, 2017 (in Japanese).
  23. [23] K. Jiang, C. Wang, H. Zhang, W. Chen, B. Zhang, Y. Tang, and F. Wu, “Damage analysis of 2008 Wenchuan earthquake using SAR images,” Proceeding of 2009 IEEE International Geoscience and Remote Sensing Symposium, pp. V-108-V-111, doi: 10.1109/IGARSS.2009.5417722, 2009.
  24. [24] T. Balz, D. Perissin, U. Soergel, and M. S. Liao, “Post–seismic infrastructure damage assessment using high-resolution SAR satellite data,” Proceedings of 2nd International Conference on Earth Observation for Global Change, 12pp., 2009.
  25. [25] T. Haraguchi and A. Iwamatsu, Detail map for the 2011 Tohoku-Oki earthquake and tsunamis, 2013 (in Japanese).
  26. [26] AIRBUS DFENCE & SPACE, Radiometric calibration of TerraSAR-X Data, [available on Jan. 28, 2018]
  27. [27] A. Lopes, R. Touzi, and E. Nezry, “Adaptive Speckle Filters and Scene Heterogeneity,” IEEE Transactions on Geoscience and Remote Sensing, Vol.28, No.6, pp. 992-1000, doi: 10.1109/36.62623, 1990.
  28. [28] Geospatial Information Authority of Japan (GSI), Fundamental Geospatial Data, [available on Jan. 28, 2018]
  29. [29] W. Liu, K. Sawa, and F. Yamazaki, “Backscattering characteristics of bridges from high-resolution X-band SAR imagery,” Proceedings of International Symposium on Remote Sensing 2017, pp. 324-327, 2017.
  30. [30] H. Hirano, F. Yamazaki, and W. Liu, “Backscattering characteristics of bridges from airborne full-polarimetrics SAR images,” Proceedings of the 38th Asia Conference on Remote Sensing, 9pp., 2017.
  31. [31] P. Nakmuenwai, F. Yamazaki, and W. Liu, “Automated extraction of inundation areas from multi-temporal dual-polarization RADARSAT-2 images of the 2011 Central Thailand Flood,” Remote Sensing, Vol.9, issue 1, No.78, doi:10.3390/rs9010078, 2017.

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