ScholarGate
Assistent
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.

Openen in MethodMindBinnenkortToepassen, vergelijken, advies krijgen
Tools & bronnen
Dia's downloaden
Leren & verkennen
VideoBinnenkort

Lees de volledige methode

Alleen voor leden

Log in met een gratis account om dit onderdeel te lezen.

Inloggen

Methodenkaart

De omgeving van verwante methoden — selecteer een knooppunt om te verkennen.

Bronnen

  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

Deze pagina citeren

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

Welke methode?

Plaats deze methode naast haar naaste verwanten en lees ze naast elkaar — de bibliotheek legt de boeken op tafel; de keuze is aan u.

Naast elkaar vergelijken

Geciteerd door

ScholarGateStreet Network Analysis (Street Network Analysis (Graph-Theoretic Measurement of Street Patterns)). Geraadpleegd op 2026-06-24 via https://scholargate.app/nl/urban-studies/street-network-analysis · Gegevensset: https://doi.org/10.5281/zenodo.20539026