Top > JDR > Development of Earthquake-Induced Building Damage Estimation M ...

single-dr.php

JDR Vol.8 No.2 pp. 346-355
(2013)
doi: 10.20965/jdr.2013.p0346

Paper:

Views over last 60 days: 425

Development of Earthquake-Induced Building Damage Estimation Model Based on ALOS/PALSAR Observing the 2007 Peru Earthquake

Masashi Matsuoka* and Miguel Estrada**

*Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Nagatsuta 4259-G3-2, Midori-ku, Yokohama 226-8502, Japan

**Japan-Peru Center for Earthquake Engineering and Disaster Mitigation (CISMID), National University of Engineering, Av. Túpac Amaru 1150, Lima 25, Peru

Received:
November 11, 2012
Accepted:
December 14, 2012
Published:
March 1, 2013
Creative Commons License
Keywords:
severe damage ratio, ALOS/PALSAR, the 2007 Peru earthquake, likelihood function, backscattering coefficient, data integration
Abstract
With the aim of developing a model for estimating building damage from synthetic aperture radar (SAR) data in the L-band, which is appropriate for Peru, we propose a regression discriminant function based on field survey data in Pisco, which was seriously damaged in the 2007 Peru earthquake. The proposed function discriminates among damage ranks corresponding to the severe damage ratio of buildings using ALOS/PALSAR imagery of the disaster area before and after the earthquake. By calculating differences in and correlations of backscattering coefficients, which were explanatory variables of the regression discriminant function, we determined an optimum window size capable of estimating the degree of damage more accurately. A normalized likelihood function for the severe damage ratio was developed based on discriminant scores of the regression discriminant function. The distribution of the severe damage ratio was accurately estimated, furthermore, from PALSAR imagery using data integration of the likelihood function with fragility functions in terms of the seismic intensity of the earthquake.
Cite this article as:
M. Matsuoka and M. Estrada, “Development of Earthquake-Induced Building Damage Estimation Model Based on ALOS/PALSAR Observing the 2007 Peru Earthquake,” J. Disaster Res., Vol.8 No.2, pp. 346-355, 2013.
Data files:
References
  1. [1] International Charter Space and Major Disaster,
    http://www. disasterscharter.org [accessed February 2012]
  2. [2] P. Gamba, A. Marazzi, and E. Costamagna, “Satellite data analysis for earthquake damage assessment,” Proc. of SPIE 3222, Earth Surface Remote Sensing (G. Cecchi, E. T. Engman, E. Zilioli (Eds.)), pp. 340-350, 1997.
  3. [3] K. Saito, R. J. S. Spence, C. Going, and M. Markus, “Using highresolution 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] H. Miura and S. Midorikawa, “Distribution of building damage in the southeastern part of Beichuan county due to the 2008 Sichuan, China, earthquake based on visual detection of satellite optical images,” Journal of Japan Association for Earthquake Engineering, Vol.10, No.3, pp. 46-57, 2010 (in Japanese with English abstract).
  5. [5] S. Matsuzaki, F. Yamazaki, M. Estrada, and C. Zavala, “Visual damage interpretation of buildings using QuickBird images following the 2007 Pisco, Peru earthquake,” Journal of Institute of Social Safety Science, No.13, pp. 407-413, 2010 (in Japanese with English abstract).
  6. [6] S. Ghosh, C. K. Huyck, M. Greene, S. P. Gill, J. Bevington, W. Svekla, R. DesRoches, and R. T. Eguchi, “Crowdsourcing for rapid damage assessment: the Global Earth Observation Catastrophe Assessment Network (GEO-CAN),” Earthquake Spectra, Vol.27, No.S1, pp. S179-S198, 2011.
  7. [7] G. A. Arciniegas, W. Bijker, N. Kerle, and V. A. Tolpekin, “Coherence- and amplitude-based analysis of seismogenic damage in Bam, Iran, using Envisat ASAR data,” Transactions on Geoscience and Remote Sensing, Vol.45, pp. 1571-1581, 2007.
  8. [8] S. Midorikawa and H. Miura, “Extraction of landslide areas due to the 2008 Iwate-Miyagi-nairiku, Japan earthquake from highresolution SAR image,” Journal of Japan Association for Earthquake Engineering, Vol.10, No.3, pp. 25-32, 2010 (in Japanese with English abstract).
  9. [9] Y. Ito and M. Hosokawa, “An estimation model of damage degree using interferometric SAR data,” IEEJ Transactions on Electronics, Information and Systems, Vol.122-C, No.4, pp. 617-623, 2002 (in Japanese with English abstract).
  10. [10] M. Matsuoka and F. Yamazaki, “Use of satellite SAR intensity imagery for detecting building areas damaged due to earthquakes,” Earthquake Spectra, Vol.20, No.3, pp. 975-994, 2004.
  11. [11] N. Nojima, M. Matsuoka, M. Sugito, and K. Ezaki, “Quantitative estimation of building damage based on data integration of seismic intensities and satellite SAR imagery,” Journal of JSCE, Division A, Vol.62, No.4, pp. 808-821, 2006 (in Japanese with English abstract).
  12. [12] M. Matsuoka and F. Yamazaki, “Comparative analysis for detecting areas with building damage from several destructive earthquakes using satellite synthetic aperture radar images,” Journal of Applied Remote Sensing, SPIE, Vol.4, 041867, 2010.
  13. [13] M. Matsuoka and N. Nojima, “Building damage estimation by integration of seismic intensity information and satellite L-band SAR imagery,” Remote Sensing, MDPI, Vol.2, No.9, pp. 2111-2126, 2010.
  14. [14] J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.2, No.2, pp. 165-168, 1980.
  15. [15] M. Estrada, C. Zavala, and Z. Aguilar, “Damage study of the Pisco, Peru earthquake using GIS and satellite images,” Proceedings of International Workshop for Safer Housing in Indonesia and Peru, 2008.
  16. [16] G. Grünthal, “European Macroseismic Scale 1998 (EMS-98),” European Seismological Commission, 1998.
  17. [17] T. Okuno, H. Kume, T. Haga, and T. Yoshizawa, “Multivariate statistical methods,” Union of Japanese Scientists and Engineers, Tokyo, Japan, pp. 259-321, 1981 (in Japanese).
  18. [18] A. Coburn and R. J. S. Spence, “Earthquake protection – chapter 9 earthquake risk modeling –,” John Wiley & Sons, p. 436, 2002.
  19. [19] K. A. Porter, K. S. Jaiswal, D. J.Wald,M. Greene, and C. Comartin, “WHE-PAGER project: a new initiative in estimating global building inventory and its seismic vulnerability,” Proc. The 14th World Conference on Earthquake Engineering, No.S23-016, 2008.
  20. [20] US Geological Survey, “ShakeMap,”
    http://earthquake.usgs.gov/eqcenter/shakemap/ [accessed February 2012]
  21. [21] US Geological Survey, “ShakeMap us2007gbcv,”
    http://earthquake.usgs.gov/eqcenter/shakemap/global/shake/2007gbcv/ [accessed June 2009]
  22. [22] K. Fujimoto and S. Midorikawa, “Empirical method for estimating J.M.A. instrumental seismic intensity from ground motion parameters using strong motion records during recent major earthquakes,” Journal of Institute of Social Safety Science, No.7, pp. 214-246, 2005 (in Japanese with English abstract)

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 18, 2024