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Construction of collaborative mapping engine for dynamic disaster and emergency response

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  • Guoqiang Peng

    (Nanjing Normal University
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province)
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)

  • Yongning Wen

    (Nanjing Normal University
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province)
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)

  • Yuting Li

    (Nanjing Normal University
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province)
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)

  • Songshan Yue

    (Nanjing Normal University
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province)
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)

  • Zhiyao Song

    (Nanjing Normal University
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province)
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)

Abstract

In the collaborative mapping of disasters, response situations and decisions, it is important to support various emergency responders with a unified platform to help in decision making and coordinating emergency action. However, most existing symbol libraries focus primarily on representing disasters and related information. These libraries lack specific symbols to map response situations and emergency decisions. For representation of dynamic disasters and response factors, these symbols support rich interactive editing after the symbols are mapped. In addition, decision making and mapping of disasters and response situations typically involve different domains of expertise and different responsibilities of map makers. It is essential to construct a collaborative mapping engine that supports disaster and emergency mapping on a collaborative platform. However, most existing methods of collaboration cannot readily support collaboration on symbols containing complex data structures or accommodate rich interactive editing operations. This article proposes a collaborative mapping engine for dynamic disasters and emergency responses. To support collaborative mapping based on complex data structures and rich interactive map symbols, it proposes a method of mapping operation replication to implement collaboration. Additionally, strategies were designed to enhance the efficiency and stability of collaboration. Finally, an experiment was conducted using the Wenchuan earthquake as an example. The results reveal that the engine can contribute to improved mapping efficiency and management during emergencies.

Suggested Citation

  • Guoqiang Peng & Yongning Wen & Yuting Li & Songshan Yue & Zhiyao Song, 2018. "Construction of collaborative mapping engine for dynamic disaster and emergency response," 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(1), pages 217-236, January.
    • Handle: RePEc:spr:nathaz:v:90:y:2018:i:1:d:10.1007_s11069-017-3045-6
    DOI: 10.1007/s11069-017-3045-6
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    References listed on IDEAS

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    1. Kulawiak, Marcin & Lubniewski, Zbigniew, 2014. "SafeCity — A GIS-based tool profiled for supporting decision making in urban development and infrastructure protection," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 174-187.
    2. Loayza, Norman V. & Olaberría, Eduardo & Rigolini, Jamele & Christiaensen, Luc, 2012. "Natural Disasters and Growth: Going Beyond the Averages," World Development, Elsevier, vol. 40(7), pages 1317-1336.
    3. Drago Bergholt & Päivi Lujala, 2012. "Climate-related natural disasters, economic growth, and armed civil conflict," Journal of Peace Research, Peace Research Institute Oslo, vol. 49(1), pages 147-162, January.
    4. Yi Lu & Jiuping Xu, 2014. "The progress of emergency response and rescue in China: a comparative analysis of Wenchuan and Lushan earthquakes," 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. 74(2), pages 421-444, November.
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    Cited by:

    1. Changfeng Jing & Yanli Zhu & Jiayun Fu & Meng Dong, 2019. "A Lightweight Collaborative GIS Data Editing Approach to Support Urban Planning," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    2. Ning Li & Na Sun & Chunxia Cao & Shike Hou & Yanhua Gong, 2022. "Review on visualization technology in simulation training system for major natural disasters," 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. 112(3), pages 1851-1882, July.
    3. Weilian Li & Jun Zhu & Yunhao Zhang & Lin Fu & Yuhang Gong & Ya Hu & Yungang Cao, 2020. "An on-demand construction method of disaster scenes for multilevel users," 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. 101(2), pages 409-428, March.

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