Evolution and simulation of coastal urban resilience based on pressure-state-response framework and Bayesian networks: a case study of Dalian, China

Abstract

Enhancing urban resilience and fostering sustainable economic development are crucial for countries to mitigate various risks. Based on the pressure-state-response (PSR) framework and Bayesian networks (BN), this study constructs a new urban resilience assessment and simulation model. First, based on the PSR framework and GIS, the spatiotemporal evolution of urban resilience is analyzed; second, the Geodetector is utilized to identify the primary factors influencing urban resilience; finally, the BN is employed to simulate various urban resilience scenarios. The results show that from 2000 to 2020, the resilience level of Dalian has been on an upward trend, evolving from a lower level in the central and western regions to a higher level, and its distribution has changed from dispersed to concentrated in the central urban area, but the regional spatial gap continues to widen; in addition, higher economic conditions and suitable population density are the dominant factors affecting urban resilience. Improving economic vitality and per capita public service levels can increase the probability of cities achieving high resilience and extremely high resilience by 8% and 12%, respectively. This study can provide valuable insights for enhancing the resilience of coastal cities and promoting regional sustainable development.