Document Type : علمی - پژوهشی

Authors

1 Professor of Remote Sensing & GIS Department., Shahid Beheshti University

2 Lecturer of Remote Sensing & GIS Dep., Shahid Beheshti University

3 M.Sc. RS & GIS, Earth Sciences Faculty, Shahid Beheshti University

Abstract

Earthquake is one of the most destructive natural disasters which frequently occurs with different intensities. Earthquakes cause severe damage to buildings, main roads and most importantly, loss of life. Detection of damaged buildings caused by such an event at the right time is a critical issue for crisis management and disaster relief. The aim of this study is to detect earthquake damaged buildings using very high resolution (VHR) satellite imagery. To achieve this result, the satellite images with very high resolution before and after the earthquake in Port-au-Prince in Haiti as well as the observed destruction map in 2010 were used. In this study, the optimum features extracted from the image were selected using correlation analysis. The buildings destroyed were classified using fuzzy inference system and the values of selected textures. Finally, the damage map obtained from the proposed algorithm was compared to the map of the area. The kappa criterion estimated from the results of the proposed method is 82% while the index- Jaccard parameter is 89.69%.

Keywords

  1. Gusella, L., Huyck, C.K., Cho, S. & Chung, H., 2004, Damage Assessment with Very-High Resolution Optical Imgery Following, December 26,2003, Bam, Iran Eartquake, University of Bologna.
  2. GEOCAN - Crowdsourced Disaster Assessment, 2011 Retrieved from: http://tomnod.com/ geocan/geocan.php..
  3. Haiti Earthquake Maps and Data, 2011, August 10, available: http://www.gelib.com/ haitiearthquake.htm.
  4. Haralick, Robert, Shanmugan, M.K., & Dinesten, Itshak, 1973, Textural Feature For Image Classification, IEEE Transaction on System Man and Cybernetics , Vol. 3, NO.6.
  5. He, Dong Chen, Wang, Li & Guiber, Jean, 1988, Texture Discrimination Based On An Optimal Utilization Of Texture Features, Pattern Recognition, Vol.21, NO. 2, 141-146.
  6. Hosmer, D.W. & Lemeshow, S., 2000, Applied Logistic Regression, John Wiley & Sons.
  7. Langrebe, David A., 2003, Signal Theory Methods in Multispectral Remote Sensing, In Use Of Texture Mesures, 381-388, Wiely.
  8. Malczewski, Jacek, 1999, GIS Multicriteria Decision Analysis, Canada: Wiley.
  9. Mansouri, Babak, Mousavi, Mehdi & Amini-Hossei, Kambod, 2004, Parcel-Based Damage Detection Using VHR Optical Data, 6th International Workshop on Remote Sensing for Disaster Applications.
  10. Erdik, M., K. S.-e.-e., 2011, Rapid Earthquake Loss Assessment after Damaging Earthquakes, Soil Dynamics and Earthquake Engineering, 247-266.
  11. Olgun, E., 2000, Izmit (Turkey) Earthquake and the Application of Change Detection Techniques for Damage Assessment Using Spot 4 Satellaite Images, ISPRS Journal of Photogrammetry and Remote Sensing.
  12. Rathje, Ellen M. & Crawford, Melba M., 2003, Earthquake Damage Identification Using High Resolution Satellite Image from The 2003 Northern Algeria, Workshop on Application of Remote Sensing for Disaster Response, 12 September.
  13. Roger Jang, J.-S. & Gulley, Ned, 1997, Fuzzy Logic Toolbox User’s Guide, The MathWorks, Inc. p.p 59-64.
  14. Sugeno, M., 1985, Industrial Applications of Fuzzy Control, Amsterdam, Elsevier Science, p 269.
  15. Tronin, A.A., 2003, Remote Sensing and Earthquakes, A Review, Scientific Research Centre for Ecological Safety..
  16. Tuceryan, mihran, 1998, Moment Based Texture Segmentation, Pattern Recognition, 654 - 668,.
  17. Vu, Thong Thuy, Matsuka, Masashi & Yamazaki, Fumio, 2003, Employment Of Lidar For Disaster Assessment, Workshop An Application Of Remote Sensing Technologist For Disaster Response, University of California.
  18. Yamazaki, F., 2004, Applications of remote sensing and GIS for damage assessment, Structural Safety and Reliability.
  19. Yamazaki, F., 2007, Applications of Remote Sensing and GIS for Damage Assessment, Structural Safety and Reliability.
  20. Yamazaki, Fumio & Kehiyama, Masayuki, 2003, Detection of Damage Due To The 2003 Bam, Iran Earthquake Using Terra- Aster imaging, Workshop an Application of Remote Sensing Technologist for Disaster Response, University of California, Septemer 12Th,.
  21. Yamazaki, Fumio, Yano, Yoshishia, Matsuoka, Masashi & Thuy, T. Vu., 2003, Visual and Automated Damage Detection for the 2003 Algeria and Bam Earthquakes Using High-Resolution Satellite Images, Workshop an Application of Remote Sensing Technologist for Disaster Response, University of California, September 12th.
  22. Zadeh, L.A., 1965, Fuzzy Sets. Information and Control, Brooklyn, NY