Multi-Dimensional Feature Measurement and Empirical Study of Urban Street Network in the Perspective of Complete Street:An Analytical Framework Based on Transportation,Society,and Nature
Streets form a large-scale,interconnected network system with multiple at-tributes.To guide the direction of planning interventions and inform detailed micro street design,it is crucial to accurately depict the network and establish a network classification system.The study introduces a street network measurement system that evaluates its transportation,social,and natural attributes,carefully considering the concept of complete streets,residents'mobility,and their interactions with the social and ecological systems.Dalian city was selected as a case study,and principal com-ponent analysis,comparative analysis,and cluster analysis were employed to evalu-ate the characteristics of different street network types.Several conclusions have been drawn.Transportation-oriented networks feature higher development density,im-proved urban forms,and closer proximity to transit stations.These features contrib-ute to the safety of the mobility system and align well with the goal of safe streets.Social-service-oriented networks exhibit location advantages,functional complexation,and interface quality,which is essential for meeting the needs of social interactions and supporting the goal of vibrant streets.Nature-oriented networks highlight signifi-cant proportions of blue-green spaces and enhanced accessibility,which facilitates ac-tivities involving the nature and fulfils the goal of green streets.Finally,deficient networks exhibit shortcomings in transportation safety,social vitality,and environmen-tal quality.This type of network can be improved by enhancing the proximity of transit stations,public facilities,and the green system.In conclusion,the paper pro-vides suggestions for street design in the context of urban renewal and the rational-ization of existing street networks.
street networktransportsocialnaturecomplete streetsbehavioral require-ments
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