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Exploring a new method to identify hidden danger space in the post-pandemic period: Taking Beian city in China as a case
Journal of Computational Methods in Sciences & Engineering ; 22(6):1887-1901, 2022.
Article in English | Academic Search Complete | ID: covidwho-2162928
ABSTRACT
COVID-19 has become a major public health emergency in the world, which seriously affects the normal operation of cities. Epidemic prevention and control is not only needed in big cities, but also in small and medium-sized cities. In view of this, the paper takes Beian city, China as the research area. This study establishes a street network model through spatial syntax, and predicts the crossing potential and arrival potential of its street network. This will play a reference role for traffic flow control in Beian city. The article uses emerging data. Through GIS spatial analysis method, we identify the hidden danger space of city. Therefore, this summarizes the places where people are easy to gather and some problems of the current situation of the city. The results show that (1) Beian bridge and Wuyuer street have a good traffic potential. The intersection of Longjiang Road and Beidahuang street and the intersection of Tianyuan North Road and Baocheng road have good accessibility. (2) The intersection of Ping'an Street and Shanghai road is a potential hidden danger space of the city, and the focus of epidemic prevention and control. (3) The coverage rate of urban community medical services to residential land is 58.61%, and the existing medical infrastructure is insufficient. Under public health emergencies, the paper will argue a new development ideas for health and safety small town planning by visualizing the hidden danger space of the city. [ FROM AUTHOR]
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Full text: Available Collection: Databases of international organizations Database: Academic Search Complete Language: English Journal: Journal of Computational Methods in Sciences & Engineering Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Academic Search Complete Language: English Journal: Journal of Computational Methods in Sciences & Engineering Year: 2022 Document Type: Article