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Process / pipelineSpatial network / street-pattern metrics

Street Network Analysis

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.

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Fontes

  1. Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139. DOI: 10.1016/j.compenvurbsys.2017.05.004

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ScholarGate. (2026, June 22). Street Network Analysis (Graph-Theoretic Measurement of Street Patterns). ScholarGate. https://scholargate.app/pt/urban-studies/street-network-analysis

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ScholarGateStreet Network Analysis (Street Network Analysis (Graph-Theoretic Measurement of Street Patterns)). Recuperado em 2026-06-24 de https://scholargate.app/pt/urban-studies/street-network-analysis · Conjunto de dados: https://doi.org/10.5281/zenodo.20539026