IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i21p13995-d955365.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/21/13995/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/21/13995/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jia Guo & Yusak Susilo & Constantinos Antoniou & Anna Pernestål Brenden, 2020. "Influence of Individual Perceptions on the Decision to Adopt Automated Bus Services," Sustainability, MDPI, vol. 12(16), pages 1-13, August.
    2. Ghadiri, Mehdi & Rassafi, Amir Abbas & Mirbaha, Babak, 2019. "The effects of traffic zoning with regular geometric shapes on the precision of trip production models," Journal of Transport Geography, Elsevier, vol. 78(C), pages 150-159.
    3. Fuqiang Zhao & Lichao Zhang & Guijun Yang & Li He & Fengyu Yan, 2017. "Application Of Cut Algorithm Based On Algebraic Connectivity To Community Detection," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-18, February.
    4. Chen, Lei & Kou, Yingxin & Li, Zhanwu & Xu, An & Wu, Cheng, 2018. "Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 754-773.
    5. Li, Jianyu & Zhou, Jie, 2007. "Chinese character structure analysis based on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 629-638.
    6. Tugrul Temel & Paul Phumpiu, 2021. "Pathways to recovery from COVID-19: characterizing input–output linkages of a targeted sector," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-24, December.
    7. Huang, Helai & Song, Bo & Xu, Pengpeng & Zeng, Qiang & Lee, Jaeyoung & Abdel-Aty, Mohamed, 2016. "Macro and micro models for zonal crash prediction with application in hot zones identification," Journal of Transport Geography, Elsevier, vol. 54(C), pages 248-256.
    8. repec:ctc:serie1:def14 is not listed on IDEAS
    9. Shichen Huang & Chunfu Shao & Juan Li & Xiong Yang & Xiaoyu Zhang & Jianpei Qian & Shengyou Wang, 2020. "Feature Extraction and Representation of Urban Road Networks Based on Travel Routes," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    10. Yang, Bo & Li, Xu & Liu, Xiangwei & He, He & Chen, Wei, 2019. "Alternating between consensus and leader selection reveals community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 693-706.
    11. Oluwatofunmi Deborah Aribisala & Sang-Guk Yum & Manik Das Adhikari & Moon-Soo Song, 2022. "Flood Damage Assessment: A Review of Microscale Methodologies for Residential Buildings," Sustainability, MDPI, vol. 14(21), pages 1-24, October.
    12. Lou, Hao & Li, Shenghong & Zhao, Yuxin, 2013. "Detecting community structure using label propagation with weighted coherent neighborhood propinquity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(14), pages 3095-3105.
    13. Asadi, Mehrnaz & Ulak, M. Baran & Geurs, Karst T. & Weijermars, Wendy, 2024. "A methodological framework to conduct joint zone-based analysis of traffic safety and accessibility," Journal of Transport Geography, Elsevier, vol. 118(C).
    14. Zhang, Dawei & Xie, Fuding & Zhang, Yong & Dong, Fangyan & Hirota, Kaoru, 2010. "Fuzzy analysis of community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5319-5327.
    15. Shen, Yi & Pei, Wenjiang & Wang, Kai & Li, Tao & Wang, Shaoping, 2008. "Recursive filtration method for detecting community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6663-6670.
    16. Gołata Elżbieta, 2016. "Shift in Methodology and Population Census Quality," Statistics in Transition New Series, Statistics Poland, vol. 17(4), pages 631-658, December.
    17. Maciej Beręsewicz, 2017. "A Two-Step Procedure to Measure Representativeness of Internet Data Sources," International Statistical Review, International Statistical Institute, vol. 85(3), pages 473-493, December.
    18. Luthi, Leslie & Pestelacci, Enea & Tomassini, Marco, 2008. "Cooperation and community structure in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 955-966.
    19. Jiao, Qing-Ju & Huang, Yan & Shen, Hong-Bin, 2015. "Community mining with new node similarity by incorporating both global and local topological knowledge in a constrained random walk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 363-371.
    20. Federico, Giovanni, 2025. "World Population 1800-1938," IFCS - Working Papers in Economic History.WH 45843, Universidad Carlos III de Madrid. Instituto Figuerola.
    21. Alfonso Montella & Vittorio Marzano & Filomena Mauriello & Roberta Vitillo & Roberto Fasanelli & Mariano Pernetti & Francesco Galante, 2019. "Development of Macro-Level Safety Performance Functions in the City of Naples," Sustainability, MDPI, vol. 11(7), pages 1-21, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:21:p:13995-:d:955365. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.