15-min pedestrian distance life circle and sustainable community governance in Chinese metropolitan cities: A diagnosis

Wenjun Ma, Ning Wang, Yuxi Li and Daniel(Jian) Sun ()
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Wenjun Ma: Shanghai Jiao Tong University
Ning Wang: Shanghai Jiao Tong University
Yuxi Li: Shanghai Jiao Tong University
Daniel(Jian) Sun: Chang’an University

Palgrave Communications, 2023, vol. 10, issue 1, 1-14

Abstract: Abstract Urban planning has shifted from “land-oriented” to “human-oriented” and metropolitan cities start to focus on 15-min life circle community planning during recent years. As multiple dimensions of living service facilities are included, proactive supervision and real-time evaluation are essential in the governance and spatial planning of large cities, referring to urban physical examination. This study proposes a community life circle diagnosis system based on multisource urban big data to evaluate the community public service facilities, in which the performance of urban living service, in terms of fairness, accessibility, and diversity were assessed, and the services related to the health and emergency facilities apart from the daily living service were investigated. Four representative Chinese megacities Beijing, Shanghai, Shenzhen, and Wuhan, were selected for the implementation and empirical analyses of the diagnosis system, which were further compared regarding the existing community life circle facility service. Then, situations in Shanghai in 2011, 2016, and 2021 were longitudinally compared to verify the influencing factors toward community life circle facilities. The results indicated that Shanghai has the highest quality of service of 15-min community life circle among the four Chinese cities, followed by Shenzhen, Wuhan, and Beijing, according to the average coverage rate of citywide living service facilities. However, the municipal government in Shanghai still needs to improve the investment in public resources in the suburbs, focusing on facilities related to elderly care, life security, and community travel. Findings of this study may assist metropolitan development with policy and funding priorities, by using urban big data together with traditional empirical data (e.g. social-economic data, built environment, etc.) to diagnose sustainable community development problems.

Date: 2023
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DOI: 10.1057/s41599-023-01812-w

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