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Street Network Analysis×Walkability Index×
领域Urban StudiesUrban Studies
方法族Process / pipelineProcess / pipeline
起源年份20172010
提出者Geoff Boeing (OSMnx); graph-theoretic street analysis traditionLawrence Frank and colleagues
类型Graph-theoretic measurement of street-network structure and connectivityComposite neighbourhood index of how supportive the built environment is of walking
开创性文献Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139. DOI ↗Frank, L. D., Sallis, J. F., Saelens, B. E., Leary, L., Cain, K., Conway, T. L., & Hess, P. M. (2010). The development of a walkability index: Application to the Neighborhood Quality of Life Study. British Journal of Sports Medicine, 44(13), 924–933. DOI ↗
别名Street Pattern Analysis, Road Network Metrics, Urban Street Connectivity Analysis, Configurational Street AnalysisFrank Walkability Index, Walk Score, Neighborhood Walkability Index, Pedestrian Environment Index
相关44
摘要Street network analysis treats a city's streets as a mathematical graph — intersections as nodes, street segments as edges — and measures its structure with graph-theoretic indicators of connectivity, density, centrality, and efficiency. From this representation come the metrics that distinguish a permeable grid from a tree-like cul-de-sac suburb: intersection density, average node degree, the share of dead-ends, betweenness centrality, and circuity (how much longer network routes are than straight lines). Tools such as Geoff Boeing's OSMnx made it routine to download, model, and analyse the street network of any place on Earth from OpenStreetMap, turning street-pattern analysis into a reproducible, comparative science of urban form.A walkability index measures how well a neighbourhood's built environment supports walking, by combining a small set of land-use and street-design variables into a single score. The influential index developed by Lawrence Frank and colleagues sums standardized measures of residential density, land-use mix, street connectivity, and retail floor-area ratio, giving extra weight to intersection density because connected street grids most strongly enable walking. Consumer tools such as Walk Score popularized the same idea by scoring an address on the proximity and variety of nearby destinations, making walkability a routine input to planning, public health, and real-estate analysis.
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ScholarGate方法对比: Street Network Analysis · Walkability Index. 于 2026-06-24 检索自 https://scholargate.app/zh/compare