Measuring the Urban Resilience Abased on Geographically Weighted Regression (GWR) Model in the Post-Pandemic Era: A Case Study of Jiangsu Province, China

Abstract

Since China declared that the post-epidemic era would begin in April 2020, the prevention and control of epidemics have become routine. The capacity of cities to respond to future public health emergencies will be enhanced if the resilience of cities is accurately measured and an emphasis is placed on improving resilience levels. Under the 4R framework, this study quantifies and analyzes the level of resilience of the cities in Jiangsu Province from both subjective and objective perspectives. By selecting explanatory variables and developing a GWR model, the spatial distribution characteristics of the quantified scores of resilience and the spatial characteristics of the influencing factors are analyzed. The results indicate that cities in southern Jiangsu should invest more in economic development and medical resources in the post-epidemic period. Northern Jiangsu should prioritize boosting the health and social work sector’s gross domestic product. Coastal cities must enhance their capacity for innocuous waste treatment.

Spatial Distribution Heterogeneity and Influencing Factors of Different Leisure Agriculture Types in the City

“…Regarding the research methodology, various methods suitable for leisure agriculture or individual types were screened. In addition, compared with popular spatial analysis methods in recent years such as geographically weighted regression [61,62], geographic detectors [63,64], spatial autocorrelation [65], etc., the study of the contribution of spatial principal component dimensionality reduction expression factors to the spatial distribution of each type of leisure agriculture is valuable and enhances the space, embodied in the combination of numerical calculations and geographical visualization. As for the influence mechanism, comparing the previous scholars analyzed the spatial distribution of leisure agriculture from the perspective of spatial measurements [66,67] and quantified the degree of government support for leisure agriculture [33,68].…”

Spatiotemporal Evolution and Influencing Factors of Tourism Economic Resilience under the Impact of COVID-19—A Case Study of Coastal Cities in China

“…The outbreak of the novel coronavirus 2019 (COVID-19) was an unprecedented public health event that had a huge impact on major economies around the world [1]. At the beginning of the pandemic, China's GDP in the first quarter of 2020 showed a negative growth of −6.8% compared to 2019.…”

“…Accurately assessing the level of tourism economic resilience before and after COVID-19 in the coastal region can provide substantial guidance and recommendations for resilience enhancements and the sustainable development of the tourism economy in the future. On this basis, this paper focuses on the following issues: (1) What are the characteristics of the spatiotemporal distribution of tourism economic resilience among coastal cities under COVID-19? (2) What are the differences in tourism economic resilience across coastal cities?…”