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  • 标题:A SDSS-Based Earthquake Damage Assessment for Emergency Response: Case Study in Bam
  • 本地全文:下载
  • 作者:M. Teimouri ; M.R. Delavar ; S. Kolyaie
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2008
  • 卷号:XXXVII-B8
  • 页码:451-456
  • 出版社:Copernicus Publications
  • 摘要:Lack of reliable, up to date, available and qualified geospatial data is one of the problems we are faced to have a proper response to natural disasters. On the other hand, complexity of earthquake phenomena from time, position and intensity, makes it a very uncertain phenomenon to assess. Furthermore, there is no comprehensive spatial analysis tool to support decision making under such disasters. Therefore, development of spatial decision support system (SDSS) to support processing and analyzing geo-spatial data for disaster management and damage estimation is of extreme importance. Previous research shows that about 70 % of Iranian urban areas are suspect to earthquake, therefore, Iran is located in an extremely earthquake risk prone areas in the world.This paper outlines a methodology to assess damage estimation due to an earthquake using SDSS. The methodology is based on quantifying number of buildings destroyed due to an earthquake using high resolution remotely sensed images and other spatial data to be integrated in a SDSS.An inventory of buildings in Bam city before the earthquake happened in Dec. 2003 was prepared. The number of destroyed buildings, due to the earthquake was evaluated. An object-based classification and segmentation methods have been used for damage estimation. Out of 18872 buildings in Bam city, 6473 buildings (34 %) were collapsed due to the earthquake. Preliminary assessments indicate an overall accuracy for the classification to be about 80.5%.The results of this paper can assist decision makers to allocate rescue forces to the damaged areas based on their degree of destruction
  • 关键词:SDSS; Earthquake; Image Classification; Rescue Management
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