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Spatial–Temporal Evolution of Urban Resilience and Its Influencing Factors: Evidence from the Guanzhong Plain Urban Agglomeration

1
School of Economics and Management, Chang’an University, Xi’an 710064, China
2
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(7), 2593; https://doi.org/10.3390/su12072593
Received: 23 January 2020 / Revised: 18 March 2020 / Accepted: 18 March 2020 / Published: 25 March 2020
(This article belongs to the Section Sustainable Urban and Rural Development)
Rapid urbanization places great pressure on the ecological environment and the carrying capacity of cities. Improving urban resilience has become an inherent requirement for the sustainable development of modern cities and urban agglomerations. This study constructed a comprehensive system to evaluate urban resilience from four perspectives: The ecological environment, economic level, social environment, and infrastructure services. As a case study, the extreme entropy method and panel data from about 16 cities from 2009 to 2016 were used to calculate resilience levels in the Guanzhong plain urban agglomeration (GPUA) in China. The spatial and temporal evolution of urban resilience characteristics in the GPUA were analyzed using ArcGIS. The influencing factors were further explored using a grey correlation analysis. The results showed that the urban resilience of GPUA experienced geographical differentiation in the “East-Central-Western” area and a “circle type” evolution process. Most urban resilience levels were low. The resilience of the infrastructure and the ecological environment significantly impacted the city and became its development weaknesses. Economic considerations have become one of the main factors influencing fluctuations in urban resilience. In summary, this study explored the differences in resilience in the GPUA and provided a reference for improving the urban resilience of other cities located in underdeveloped regions. The study also provided a useful theoretical basis for sustainable urban development. View Full-Text
Keywords: urban agglomeration; urban resilience; extreme entropy method; grey correlation degree; spatial–temporal evolution urban agglomeration; urban resilience; extreme entropy method; grey correlation degree; spatial–temporal evolution
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Ma, F.; Wang, Z.; Sun, Q.; Yuen, K.F.; Zhang, Y.; Xue, H.; Zhao, S. Spatial–Temporal Evolution of Urban Resilience and Its Influencing Factors: Evidence from the Guanzhong Plain Urban Agglomeration. Sustainability 2020, 12, 2593.

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