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Optimizing Emergency Shelter Selection in Earthquakes Using a Risk-Driven Large Group Decision-Making Support System

Author

Listed:
  • Amir Reza Bakhshi Lomer

    (Department of Geography, Birkbeck University of London, London WC1E 7HX, UK)

  • Mahdi Rezaeian

    (Department of Geographic Information System Engineering, College of Engineering, University of Tehran, Tehran 1439957131, Iran)

  • Hamid Rezaei

    (Department of Civil and Environmental Engineering, Florida International University, Miami, FL 33174, USA)

  • Akbar Lorestani

    (Faculty of Geography, University of Tehran, Tehran 1417935840, Iran)

  • Naeim Mijani

    (Department of Remote Sensing and GIS, University of Tehran, Tehran 1417853933, Iran)

  • Mohammadreza Mahdad

    (Detailed Planning of Urban Development Vice-Chancellor, Isfahan 1st District Municipality, Isfahan 8145913151, Iran)

  • Ahmad Raeisi

    (Department of Electrical and Computer Engineering, University of Tehran, Tehran 1439957131, Iran)

  • Jamal Jokar Arsanjani

    (Geoinformatics Research Group, Department of Planning and Development, Aalborg University Copenhagen, DK-2450 Copenhagen, Denmark)

Abstract

This study presents a novel risk-based decision support system for helping disaster risk management planners select the best locations for emergency shelters after an earthquake. The system starts by identifying 18 criteria, based on stakeholder analysis, that are important for selecting shelter sites. These criteria are then standardized to reflect their importance in the site selection process. Next, a Large Group Decision-Making (LGDM) model is used to determine the weight of each criterion based on collective intelligence. Finally, the Ordered Weighted Average (OWA) method is used to assess the suitability of different geographical locations for emergency shelters, resulting in a suitability map. The factors that were most significant for selecting the best emergency shelters were the distance from the fault, population density, access to green spaces, and building quality. The area of the optimal sites for emergency shelters in the region varied depending on the decision-maker’s risk attitude, ranging from 4% in an extremely pessimistic scenario to 28% in an extremely optimistic scenario. This system combines Geographic Information Systems (GIS) and LGDM to help decision-makers identify the optimal sites for emergency shelters under different risk levels, which can contribute to better-informed decision-making regarding disaster resilience.

Suggested Citation

  • Amir Reza Bakhshi Lomer & Mahdi Rezaeian & Hamid Rezaei & Akbar Lorestani & Naeim Mijani & Mohammadreza Mahdad & Ahmad Raeisi & Jamal Jokar Arsanjani, 2023. "Optimizing Emergency Shelter Selection in Earthquakes Using a Risk-Driven Large Group Decision-Making Support System," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4019-:d:1077046
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    References listed on IDEAS

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    1. Hamid Rezaei & Elżbieta Macioszek & Parisa Derakhshesh & Hassan Houshyar & Elias Ghabouli & Amir Reza Bakhshi Lomer & Ronak Ghanbari & Abdulsalam Esmailzadeh, 2023. "A Spatial Decision Support System for Modeling Urban Resilience to Natural Hazards," Sustainability, MDPI, vol. 15(11), pages 1-18, May.

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