Towards Rapid Citywide Damage Mapping Using Neighborhood Edge Dissimilarities in Very High-Resolution Optical Satellite Imagery—Application to the 2003 Bam, Iran, Earthquake-Reference-Cited by-同舟云学术

Towards Rapid Citywide Damage Mapping Using Neighborhood Edge Dissimilarities in Very High-Resolution Optical Satellite Imagery—Application to the 2003 Bam, Iran, Earthquake

Published:2005-12 Issue:1_suppl Volume:21 Page:255-266
ISSN:8755-2930
Container-title:Earthquake Spectra
language:en
Short-container-title:Earthquake Spectra

Author:

Huyck Charles K.¹,Adams Beverley J.²,Cho Sungbin³,Chung Hung-Chi⁴,Eguchi Ronald T.⁵

Affiliation:

1. Senior Vice President, ImageCat, Inc. 400 Oceangate, Suite 1050, Long Beach, CA 90802

2. Remote Sensing Group Leader, ImageCat, Inc. 400 Oceangate, Suite 1050, Long Beach, CA 90802

3. Transportation Systems Analyst, ImageCat, Inc. 400 Oceangate, Suite 1050, Long Beach, CA 90802

4. Project Engineer, ImageCat, Inc. 400 Oceangate, Suite 1050, Long Beach, CA 90802

5. President and CEO, ImageCat, Inc. 400 Oceangate, Suite 1050, Long Beach, CA 90802

Abstract

Remote sensing technology is increasingly recognized as a valuable post-earthquake damage assessment tool. Recent studies performed by research teams in the United States, Japan, and Europe have demonstrated that building damage sustained in urban environments can be identified through analysis of optical imagery and synthetic aperture radar (SAR) data. Damage detection using automated change detection algorithms will soon facilitate the scaling and prioritization of relief efforts, as well as the monitoring of the recovery operations. This paper introduces the use of an edge dissimilarity algorithm to quantify the extent of building damage.

Publisher

SAGE Publications

Subject

Geophysics,Geotechnical Engineering and Engineering Geology

Link

http://journals.sagepub.com/doi/pdf/10.1193/1.2101907

Reference18 articles.

1. Adams, B. J., Huyck, C. K., and Eguchi, R. T. , 2003a. The Boumerdes (Algeria) earthquake of May 21, 2003: Preliminary reconnaissance using remotely sensed data, URL: http://mceer.buffalo.edu/research/boumerdes/default.asp.

2. Adams, B. J., Huyck, C. K., Eguchi, R. T., Yamazaki, F., and Estrada, M. , 2003b. Post-earthquake reconnaissance using satellite imagery: Boumerdes case study,The Boumerdes, Algeria, Earthquake May 21, 2003, EERI, Oakland, Insert pp. 1–8.

3. Adams, B. J., Huyck, C. K., Mansouri, B., Eguchi, R. T., and Shinozuka, M. , 2004. Application of high-resolution optical satellite imagery for post-earthquake damage assessment: The 2003 Boumerdes (Algeria) and Bam (Iran) earthquakes,MCEER Research Progress and Accomplishments 2003–2004, Multidisciplinary Center for Earthquake Engineering Research, Buffalo, NY, pp. 173–186.

4. Adams, B. J., Mansouri, B., and Huyck, C. K. , 2005. Streamlining post-earthquake data collection and damage assessment in Bam, using VIEWS (Visualizing Impacts of Earthquakes With Satellites), Special Issue 1,2005 Bam, Iran, Earthquake Reconnaissance Report. Edited by Farzad Naeim et al. ,Earthquake Spectra21(S1) (Section 5 of this issue), December.

5. Agresti, A., and Finlay, B. , 1997.Statistical Methods for the Social Sciences, 3d ed. Chapter 15, Prentice Hall, NJ.

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