Analysis of the Spatial Distribution Characteristics of Urban Resilience and Its Influencing Factors: A Case Study of 56 Cities in China

Maomao Zhang, Weigang Chen, Kui Cai, Xin Gao, Xuesong Zhang, Jinxiang Liu, Zhiyuan Wang and Deshou Li
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Maomao Zhang: Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China
Weigang Chen: School of Architecture, University of South China, Hengyang 421001, China
Kui Cai: Institute of Geological Survey, Hebei GEO University, Shijiazhuang 050031, China
Xin Gao: Business School, Hohai University, Nanjing 211100, China
Xuesong Zhang: Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China
Jinxiang Liu: School of Civil Engineering, University of South China, Hengyang 421001, China
Zhiyuan Wang: School of Architecture, University of South China, Hengyang 421001, China
Deshou Li: Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China

IJERPH, 2019, vol. 16, issue 22, 1-22

Abstract: The healthy development of the city has received widespread attention in the world, and urban resilience is an important issue in the study of urban development. In order to better provide a useful reference for urban resilience and urban health development, this paper takes 56 cities in China as the research object, and selects 29 indicators from urban infrastructure, economy, ecology and society. The combination weight method, exploratory spatial data analysis (ESDA) and spatial measurement model are used to explore the spatial distribution of urban resilience and its influencing factors. From 2006 to 2017, the urban resilience of prefecture-level cities in the four provinces showed a wave-like rise. During the study period, the urban resilience values, measured as Moran’s Is, were greater than 0.3300, showing a significantly positive correlation in regard to their spatial distribution. Regarding the local spatial correlation, the urban resilience of the study area had spatial agglomeration characteristics within the province, with a significant distribution of “cold hot spots” in the spatial distribution. From the perspective of the factors that affected urban resilience, the proportion of the actual use of foreign capital in GDP and carbon emissions per 10,000 CNY of GDP had a negative impact and GDP per square kilometer, the proportion of urban pension insurance coverage, the proportion of the population with higher education, and expenditure to maintain and build cities had a positive impact. The development strategy of urban resilience must be combined with the actual situation of the region, and the rational resilience performance evaluation system and the top-level design of urban resilience improvement should be formulated to comprehensively improve urban resilience.

Keywords: urban resilience; spatial distribution; influencing factor; spatial regression model; 56 cities (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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