Construction of collaborative mapping engine for dynamic disaster and emergency response |
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Authors: | Guoqiang Peng Yongning Wen Yuting Li Songshan Yue Zhiyao Song |
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Affiliation: | 1.Key Laboratory of Virtual Geographic Environment (Ministry of Education),Nanjing Normal University,Nanjing,China;2.State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province),Nanjing,China;3.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing,China |
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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. |
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