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Research On The Spatiotemporal Evolution And Driving Factors Of Multi-scale Urban Resilienc

Posted on:2024-05-26Degree:MasterType:Thesis
Country:ChinaCandidate:M ChaoFull Text:PDF
GTID:2530307130460594Subject:Resources and Environment
Abstract/Summary:PDF Full Text Request
In the context of global urbanization,various uncertain risks have caused serious obstacles to the development of cities.Urban resilience can be used as an indicator to measure the ability of cities to cope with the impact of various risks on cities.It is of great significance to carry out research on urban resilience for promoting the sustainable development of cities.Guanshanhu District of Guiyang City,Guizhou Province,China is taken as the research area in this paper.Starting from multiple scales such as street,grid,and community,the entropy method is adopted to construct a comprehensive evaluation index system of urban resilience including four dimensions such as ecology resilience subsystem,economy resilience subsystem,society resilience subsystem,and facilities resilience subsystem.Then,the spatial and temporal evolution trend and differentiation pattern of urban resilience and its subsystems are studied.Finally,the interaction mechanism of the driving factors behind urban resilience was identified by the geodetector model.The main work and achievements of this paper are as follows:(1)As the current research on macro-scale urban resilience focuses on urban coordination from a holistic perspective,it is difficult to provide practical guidance for micro-scale urban resilience improvement.In this paper,building density,land mixing degree,transportation accessibility,and other indicators are introduced to construct a set of micro-scale urban resilience evaluation models.The results of the model show that the economic resilience subsystem,which contributes significantly in large-scale studies,is not outstanding in the paper,while the ecological resilience and facility resilience subsystems,which reflect the daily needs of urban residents,contribute more,indicating that the capacity characteristics of small-scale urban resilience are different from those of large-scale urban resilience.This paper is a helpful supplement to the empirical research on micro-scale urban resilience.(2)This paper analyzes the spatio-temporal evolution trend of urban resilience and its subsystems in multiple dimensions,such as streets,grids,and community,making up for the defects that most current studies start from a single scale and ignore the correlation and nesting of urban resilience at different scales.The results show that the urban resilience of Guanshanhu District is improved significantly,and the grid scale resilience level is higher,while the street and community scale resilience level is lower.Urban resilience generally presents a "core-periphery" spatial pattern,but the distribution range of horizontal units of resilience at different scales is not completely consistent,and the "scale effect" has a significant impact on urban resilience.(3)Standard deviation ellipse,Theil index,and spatial autocorrelation analysis were used to study the morphological evolution,spatial difference,and differentiation pattern of urban resilience and its subsystems at different scales in Guanshan Lake District.The results show that the spatial distribution of urban resilience is relatively stable.The unbalanced development inside the eastern streets is the key to restricting the improvement of urban resilience.Urban resilience showed a strong spatial positive correlation in the whole range.There were high-high,low-low,high-low,and low-high clustering types in the local range,and the spatial differentiation was obvious.(4)The mechanism of single and interactive driving factors behind the urban resilience of various scales in the Guanshan Lake District was identified with the help of geodetector.The detection results show that: The single factors with the strongest explanatory power for street,grid,and community scale are financial institutions,slope,and air quality,while the interaction factors with the strongest explanatory power are financial institutions with government institutions,land function mixing degree with transportation accessibility,and economic development with building density,respectively,indicating that urban resilience is the result of the combined action of various driving factors.The interaction between different factors can enhance the explanatory power of urban resilience.
Keywords/Search Tags:Urban resilience, Spatio-temporal evolution, Driving factors, Geodetector, Guanshanhu district
PDF Full Text Request
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