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Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-73
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 10 Apr 2018

Research article | 10 Apr 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

An Automated Technique for Damage Mapping after Earthquakes by Detecting Changes between High-Resolution Images

Tianyu Ci1, Zhen Liu2, Ying Wang3, Qigen Lin4, and Di Wu5 Tianyu Ci et al.
  • 1College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
  • 2Center of Information and Network Technology, Beijing Normal University, Beijing, China
  • 3Key Laboratory of Environmental Change and Natural Disaster of MOE, Beijing Normal University, Beijing, China
  • 4Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China
  • 5Heilongjiang Geomatics center of China Bureau of Surveying and maping, Harbin, China

Abstract. Improving the speed and accuracy of earthquake disaster loss evaluations is very important for disaster response and rescue. This paper presents a new method for urban damage assessments after earthquake disasters by using a change detection technique between bi-temporal (pre- and post-event) high-resolution optical images. A similarity index derived from a pair of images was used to extract the characteristics of collapsed buildings. In this paper, the methods are illustrated using two case studies. Our results confirmed the effectiveness and precision of the proposed technique with optical data of the damage presented using a block scale.

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Short summary
Improving the speed and accuracy of earthquake disaster loss evaluations is very important for disaster response and rescue. This paper presents a new method for urban damage assessments after earthquake disasters by using a change detection technique between bi-temporal (pre- and post-event) high-resolution optical images.
Improving the speed and accuracy of earthquake disaster loss evaluations is very important for...
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