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Population evacuation analysis: considering dynamic population vulnerability distribution and disaster information dissemination

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Abstract

Knowing the dynamic population vulnerability distribution and having an efficient information dissemination of disaster warnings play a very important role in the developing of a population evacuation strategy. In this paper, the evacuation of populations in a densely populated area of Beijing was studied with consideration of the spatio-temporal population vulnerability distribution and different methods of disaster information dissemination. Firstly, the population vulnerability distribution was obtained based on the population density, with consideration for dynamic population distribution, building heights, building types and population characteristics. Secondly, a disaster information dissemination model that utilizes sound trucks was developed, and an improved algorithm for finding the optimal route for the sound trucks was established. Thirdly, we ran 81 evacuation simulations that included different variables such as time periods, number of sound trucks, speeds of trucks and sound-spread radius. These were performed based on the dynamic population vulnerability distribution and the developed model. Through these simulations, the rates of population congestion in an evacuation area were understood, and an optimized evacuation plan was obtained and analyzed. The process and the results that were obtained are essential for improving the efficiency of evacuations, which should considerably reduce the possibility injury, deaths and other losses in a disaster.

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Acknowledgments

This work was supported by National Natural Science Foundation of China under (Grant No. 71173128, 91224008) and Ministry of Science and Technology of the People’s Republic of China under Grant No. 2011BAK07B02.

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Correspondence to Hong Huang.

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Zhang, N., Huang, H., Su, B. et al. Population evacuation analysis: considering dynamic population vulnerability distribution and disaster information dissemination. Nat Hazards 69, 1629–1646 (2013). https://doi.org/10.1007/s11069-013-0767-y

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