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Developing an Automated Analytical Process for Disaster Response and Recovery in Communities Prone to Isolation

Author

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  • Byungyun Yang

    (Department of Geography Education, Dongguk University, Seoul 04620, Korea)

  • Minjun Kim

    (Department of Geography, Kyung Hee University, Seoul 02447, Korea)

  • Changkyu Lee

    (Department of Geography, Kyung Hee University, Seoul 02447, Korea)

  • Suyeon Hwang

    (Department of Geography, Kyung Hee University, Seoul 02447, Korea)

  • Jinmu Choi

    (Department of Geography, Kyung Hee University, Seoul 02447, Korea)

Abstract

Today, unpredictable damage can result from extreme weather such as heat waves and floods. This damage makes communities that cannot respond quickly to disasters more vulnerable than cities. Thus, people living in such communities can easily become isolated, which can cause unavoidable loss of life or property. In the meantime, many disaster management studies have been conducted, but studies on effective disaster response for areas surrounded by mountains or with weak transportation infrastructure are very rare. To fill the gap, this research aimed at developing an automated analysis tool that can be directly used for disaster response and recovery by identifying in real time the communities at risk of isolation using a web-based geographic information system (GIS) application. We first developed an algorithm to automatically detect communities at risk of isolation due to disaster. Next, we developed an analytics module to identify buildings and populations within the communities and efficiently place at-risk residents in shelters. In sum, the analysis tool developed in this study can be used to support disaster response decisions regarding, for example, rescue activities and supply of materials by accurately detecting isolated areas when a disaster occurs in a mountainous area where communication and transportation infrastructure is lacking.

Suggested Citation

  • Byungyun Yang & Minjun Kim & Changkyu Lee & Suyeon Hwang & Jinmu Choi, 2022. "Developing an Automated Analytical Process for Disaster Response and Recovery in Communities Prone to Isolation," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:21:p:13995-:d:955365
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    References listed on IDEAS

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    1. Chul Sue Hwang & Seong-Yun Hong & TaeKeon Hwang & Byungyun Yang, 2020. "Strengthening the Statistical Summaries of Economic Output Areas for Urban Planning Support Systems," Sustainability, MDPI, vol. 12(14), pages 1-21, July.
    2. Bernard Baffour & Thomas King & Paolo Valente, 2013. "The Modern Census: Evolution, Examples and Evaluation," International Statistical Review, International Statistical Institute, vol. 81(3), pages 407-425, December.
    3. I.-J. Moon & I. Oh & T. Murty & Y.-H. Youn, 2003. "Causes of the Unusual Coastal Flooding Generated by Typhoon Winnie on the West Coast of Korea," 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. 29(3), pages 485-500, July.
    4. Ji-Myong Kim & Taehui Kim & Kiyoung Son & Sang-Guk Yum & Sungjin Ahn, 2019. "Measuring Vulnerability of Typhoon in Residential Facilities: Focusing on Typhoon Maemi in South Korea," Sustainability, MDPI, vol. 11(10), pages 1-11, May.
    5. Capocci, A. & Servedio, V.D.P. & Caldarelli, G. & Colaiori, F., 2005. "Detecting communities in large networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(2), pages 669-676.
    6. Abdel-Aty, Mohamed & Lee, Jaeyoung & Siddiqui, Chowdhury & Choi, Keechoo, 2013. "Geographical unit based analysis in the context of transportation safety planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 62-75.
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