RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2022, Vol. 31 >> Issue (9): 1975-1987.doi: 10.11870/cjlyzyyhj202209010

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Spatial-temporal Analysis and Influencing Factors of Ecological Resilience in Yangtze River Delta

TAO Jie-yi1, DONG Ping1, LU Yu-qi1,2,3   

  1. (1. College of Geography Science, Nanjing Normal University Nanjing, Nanjing 210023, China; 2. College of Rural Vitalization, Nanjing Normal University Nanjing, Nanjing 210023, China; 3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University Nanjing, Nanjing 210023, China)
  • Online:2022-09-20 Published:2022-09-29

Abstract: Urban ecological resilience construction is the key for the high-quality integrated development of the Yangtze River Delta. This paper constructs an ecological resilience evaluation model from the three dimensions of resistance, adaptability and recovery to study the spatial- temporal evolution characteristics of urban ecological resilience in the Yangtze River Delta from 2011 to 2019; and analyzes the spatial-temporal heterogeneity of ecological resilience influencing factors by using the geographically and temporally weighted regression (GTWR) and STIRPAT (the Stochastic Impacts by Regression on Population, Affluence, and Technology) extended models. The results show that: (1) From 2011 to 2019, the ecological resilience index of Yangtze River Delta cties showed an overall fluctuating upward trend, with the number of fluctuating declining or stagnant cities accounting for a small proportion and the fluctuating low-rate rising cities dominating; the resistance of ecological resilience of cities was higher than the adaptability and recovery, and the resistance of ecological resilience showed a fluctuating downward trend during the study period while the adaptability and recovery fluctuated upward. (2) The ecological resilience high value zone of the Yangtze River Delta experienced the evolution process of “overall dispersion and partial agglomeration-small agglomeration and large dispersion-small agglomeration and large dispersion strengthening-Multi-location clustering”. (3) The results of the GTWR model showed that there were obvious spatial and temporal differences among the influencing factors, and the intensity and fluctuation direction of the influencing factors varied in different regions.

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