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Using high-resolution satellite imagery to provide a relief priority map after earthquake

Author

Listed:
  • Hamid Reza Ranjbar

    (Malek Ashtar University of Technology)

  • Alireza A. Ardalan

    (University of Tehran)

  • Hamid Dehghani

    (Malek Ashtar University of Technology)

  • Mohammad Reza Saradjian

    (University of Tehran)

Abstract

After the earthquake occurrence, collecting correct information about the extent of damage is essential for managing critical conditions and allocating limited resources. The prepared building damage maps sometimes bring about waste of time required for rescuing individuals under the rubble by wrongly conducting rescue teams toward regions with a lower rescue priority. In this research, an algorithm based on using a proposed standard at database level was developed to prioritize damaged buildings by considering five key elements of land use type, the degree of damage to buildings, the land use differentiation index, time of the highest population density in each land use, and time of disaster’s incidence. The steps of the proposed method which was implemented in the MATLAB environment include: detecting buildings on the pre- and post-event imagery, implementing texture features for each candidate building, choosing the optimal features by genetic algorithm, determining the degree of building damage in three classes of negligible damage, substantial damage, and heavy damage by using the difference between chosen features as inputs of the designed neurofuzzy inference system. Data collected from field observations were compared to the output obtained from the proposed algorithm. This comparison presented a general accuracy of 88% and Kappa coefficient of 79% in the classification of buildings into three damage classes. The proposed standard then was used for classifying damaged buildings into relief priorities of high, medium, and low. Findings revealed that the relief priority map could be a basis for correct guidance of relief and rescue teams during crucial times following earthquakes.

Suggested Citation

  • Hamid Reza Ranjbar & Alireza A. Ardalan & Hamid Dehghani & Mohammad Reza Saradjian, 2018. "Using high-resolution satellite imagery to provide a relief priority map after earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(3), pages 1087-1113, February.
  • Handle: RePEc:spr:nathaz:v:90:y:2018:i:3:d:10.1007_s11069-017-3085-y
    DOI: 10.1007/s11069-017-3085-y
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    References listed on IDEAS

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    1. Tienan Feng & Zhonghua Hong & Hengjing Wu & Qiushi Fu & Chaoxin Wang & Chenghua Jiang & Xiaohua Tong, 2013. "Estimation of earthquake casualties using high-resolution remote sensing: a case study of Dujiangyan city in the May 2008 Wenchuan earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(3), pages 1577-1595, December.
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    Cited by:

    1. Quoc Dung Cao & Youngjun Choe, 2020. "Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3357-3376, September.

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