Measurement of urban resilience level and identification of obstacle factors in urban agglomeration
Urban agglomeration represents the pinnacle of urban development spatially.Enhancing urban resilience is paramount for fostering resilient cities and nurturing sustainable,healthy urban agglomerations.This paper endeavors to comprehensively gauge the urban resilience level of urban agglomerations and pinpoint obstacle factors.To this end,an urban agglomeration urban resilience evaluation index system was constructed,employing the entropy method and the BP neural network model to assess the resilience and composite performance of each city subsystem within the Guanzhong Plain urban agglomeration from 2011 to 2020.Through systematic analysis,the obstacle degree model was utilized to identify factors impeding urban resilience in the Guanzhong Plain urban agglomeration.The study reveals that the urban resilience of the Guanzhong Plain urban agglomeration rests at a medium level,with a general upward trajectory.Spatially,its distribution pattern exhibits an inverted V-shape,with lower resilience in the east and west,and higher resilience in the middle.Economic system resilience leans towards lower and medium levels,while social system resilience tends to be medium to higher.Ecosystem resilience predominantly falls within higher levels,while infrastructure system resilience spans between lower and higher levels.Notably,the primary obstacles hampering urban resilience improvement in the Guanzhong Plain urban agglomeration are the green coverage rate of built-up areas and society-wide electricity consumption.From a subsystem perspective,the social system consistently emerges as the key constraint on urban resilience improvement in this agglomeration.To address these challenges,urban agglomerations should intensify inter-city cooperation,facilitate information sharing,uplift living standards,bolster urban infrastructure construction,and perpetually drive coordinated development across urban agglomerations.
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