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Identifying Evacuation Needs and Resources Based on Volunteered Geographic Information: A Case of the Rainstorm in July 2021, Zhengzhou, China

Author

Listed:
  • Jingyi Gao

    (Department of Architecture and Building Science, Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan)

  • Osamu Murao

    (International Research Institute of Disaster Science, Tohoku University, Sendai 980-8572, Japan)

  • Xuanda Pei

    (Department of Earth Science, Graduate School of Science, Tohoku University, Sendai 980-8578, Japan)

  • Yitong Dong

    (Department of Architecture and Building Science, Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan)

Abstract

Recently, global climate change has led to a high incidence of extreme weather and natural disasters. How to reduce its impact has become an important topic. However, the studies that both consider the disaster’s real-time geographic information and environmental factors in severe rainstorms are still not enough. Volunteered geographic information (VGI) data that was generated during disasters offered possibilities for improving the emergency management abilities of decision-makers and the disaster self-rescue abilities of citizens. Through the case study of the extreme rainstorm disaster in Zhengzhou, China, in July 2021, this paper used machine learning to study VGI issued by residents. The vulnerable people and their demands were identified based on the SOS messages. The importance of various indicators was analyzed by combining open data from socio-economic and built-up environment elements. Potential safe areas with shelter resources in five administrative districts in the disaster-prone central area of Zhengzhou were identified based on these data. This study found that VGI can be a reliable data source for future disaster research. The characteristics of rainstorm hazards were concluded from the perspective of affected people and environmental indicators. The policy recommendations for disaster prevention in the context of public participation were also proposed.

Suggested Citation

  • Jingyi Gao & Osamu Murao & Xuanda Pei & Yitong Dong, 2022. "Identifying Evacuation Needs and Resources Based on Volunteered Geographic Information: A Case of the Rainstorm in July 2021, Zhengzhou, China," IJERPH, MDPI, vol. 19(23), pages 1-21, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:16051-:d:989648
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    References listed on IDEAS

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    1. Rui-Song Quan, 2014. "Rainstorm waterlogging risk assessment in central urban area of Shanghai based on multiple scenario simulation," 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. 73(3), pages 1569-1585, September.
    2. Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," 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. 81(1), pages 23-40, March.
    3. Olszewski, Robert & Wendland, Agnieszka, 2021. "Digital Agora – Knowledge acquisition from spatial databases, geoinformation society VGI and social media data," Land Use Policy, Elsevier, vol. 109(C).
    4. Katerina Tzavella & Alexander Fekete & Frank Fiedrich, 2018. "Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne, Germany," 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. 91(1), pages 29-57, April.
    5. Pujun Liang & Wei Xu & Yunjia Ma & Xiujuan Zhao & Lianjie Qin, 2017. "Increase of Elderly Population in the Rainstorm Hazard Areas of China," IJERPH, MDPI, vol. 14(9), pages 1-17, August.
    6. Yang Xiao & Beiqun Li & Zaiwu Gong, 2018. "Real-time identification of urban rainstorm waterlogging disasters based on Weibo big data," 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. 94(2), pages 833-842, November.
    7. Xingqi Zhang & Maochuan Hu & Gang Chen & Youpeng Xu, 2012. "Urban Rainwater Utilization and its Role in Mitigating Urban Waterlogging Problems—A Case Study in Nanjing, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3757-3766, October.
    8. Jinping Zhang & Hang Zhang & Hongyuan Fang, 2022. "Study on Urban Rainstorms Design Based on Multivariate Secondary Return Period," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2293-2307, May.
    9. Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," 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. 81(1), pages 23-40, March.
    10. Stathis G. Arapostathis, 2021. "A Methodology for Automatic Acquisition of Flood‐event Management Information From Social Media: the Flood in Messinia, South Greece, 2016," Information Systems Frontiers, Springer, vol. 23(5), pages 1127-1144, September.
    11. Jingming Hou & Nie Zhou & Guangzhao Chen & Miansong Huang & Guangbi Bai, 2021. "Rapid forecasting of urban flood inundation using multiple machine learning models," 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. 108(2), pages 2335-2356, September.
    12. Junfei Chen & Liming Liu & Jinpeng Pei & Menghua Deng, 2021. "An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China," 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. 107(3), pages 2671-2692, July.
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