Analysis on the spatial-temporal evolution of urban agglomeration resilience: A case study in Chengdu-Chongqing Urban Agglomeration, China

Abstract

An accurate assessment of urban resilience can provide decision-makers with a better understanding of urban resilience and valuable references for developing relevant urban resilience development strategies. However, most works of existing literature focus on evaluating urban resilience from a static perspective and few studies focus on the spatio-temporal evolution characteristics of urban resilience. Therefore, an urban resilience measurement model combined with the BP neural network with a genetic algorithm is established. The Chengdu-Chongqing Urban Agglomeration is taken as a case study. In addition, the spatial-temporal evolution is analyzed by the convergence model to explore the difference among the cities in Chengdu-Chongqing Urban Agglomeration. The main results of this study show that: (1) the distribution of urban resilience in Chengdu-Chongqing Urban Agglomeration has a double-headed structure, which differs from other urban agglomerations in China. (2) the four subsystems of resilience reveal exciting results that the ecological, economic and social resilience in the Chengdu-Chongqing urban agglomeration all presented a polarized pattern, and the infrastructure resilience is balanced. (3) The temporal evolution of urban agglomeration resilience indicates that the resilience gap between cities in Chengdu-Chongqing Urban Agglomeration is narrowing from 2011 to 2019.