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• W3200978933 startingPage "2364" @default.
• W3200978933 abstract "Abstract Based on 2012–2017 panel data of 282 China’s cities, this paper uses the entropy method to calculate an urban resilience index, uses spatial cold–hot spots model to explore spatial characteristics of urban resilience, uses revised the gravity model to construct urban resilience spatial network characteristics, and uses the social network analysis method to analyze spatial network characteristics of urban resilience. The results show that: (1) Urban resilience of China’s cities has been gradually improved, and there is a geographical aggregation effect, with significant changes in hot spots and insignificant changes in cold spots. (2) Urban resilience has obvious spatial correlation and linkage effects and strong temporal fluctuation. The cities with higher degree centrality and closeness centrality are consistent in spatial distribution, mostly located in Bohai Rim, Pan‐Yangtze River Delta, Pearl River Delta and some central regions. The centrality obviously shows non‐equilibrium in spatial distribution. The cities with high centrality are mostly provincial capitals. (3) The “club effect” has not yet been reflected in the urban resilience spatial network, and the advantages of different regions are obviously different. Therefore, it is necessary to face up to the spatial difference of urban development and enhance the diversity and pertinence of urban resilience construction." @default.
• W3200978933 created "2021-09-27" @default.
• W3200978933 creator A5051306376 @default.
• W3200978933 creator A5062941485 @default.
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• W3200978933 date "2021-09-16" @default.
• W3200978933 modified "2023-10-12" @default.
• W3200978933 title "Spatiotemporal evolution and spatial relevance of urban resilience: Evidence from cities of China" @default.
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• W3200978933 doi "https://doi.org/10.1111/grow.12554" @default.
• W3200978933 hasPublicationYear "2021" @default.
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