Spatiotemporal evolution and spatial relevance of urban resilience: Evidence from cities of China
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 chara...
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| Published in | Growth and change Vol. 52; no. 4; pp. 2364 - 2390 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Lexington
Blackwell Publishing Ltd
01.12.2021
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| 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. |
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| AbstractList | 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. |
| Author | Shi, Tao Zhou, Qian Qiao, Yurong |
| Author_xml | – sequence: 1 givenname: Tao surname: Shi fullname: Shi, Tao organization: CPC Central Party School (National School of Administration) – sequence: 2 givenname: Yurong surname: Qiao fullname: Qiao, Yurong organization: Zhengzhou University of Light Industry – sequence: 3 givenname: Qian orcidid: 0000-0002-2319-1095 surname: Zhou fullname: Zhou, Qian email: zhouqian200912@163.com organization: Zhongnan University of Economics and Law |
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| Title | Spatiotemporal evolution and spatial relevance of urban resilience: Evidence from cities of China |
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