方法对比

	Spatial Design Network Analysis (sDNA)	Street Network Analysis
领域	Urban Studies	Urban Studies
方法族	Process / pipeline	Process / pipeline
起源年份	2020	2017
提出者	Crispin H. V. Cooper & Alain J. F. Chiaradia	Geoff Boeing (OSMnx); graph-theoretic street analysis tradition
类型	Link-based spatial network analysis of street and path networks	Graph-theoretic measurement of street-network structure and connectivity
开创性文献	Cooper, C. H. V., & Chiaradia, A. J. F. (2020). sDNA: 3-d spatial network analysis for GIS, CAD, Command Line & Python. SoftwareX, 12, 100525.	Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139.
别名	sDNA, Spatial Design Network Analysis, Link-Based Network Analysis, 3D Spatial Network Analysis	Street Pattern Analysis, Road Network Metrics, Urban Street Connectivity Analysis, Configurational Street Analysis
相关	4	4
摘要	Spatial Design Network Analysis (sDNA) is a toolkit for analysing street and path networks as link-based spatial graphs, measuring how individual road segments function as routes and destinations within the larger network. Developed by Crispin Cooper and Alain Chiaradia at Cardiff University, it computes closeness- and betweenness-style measures over geometrically accurate, optionally three-dimensional networks, using hybrid distance metrics that blend metric length, angular turn cost and topological steps. By weighting links and analysing them within chosen radii, sDNA predicts pedestrian and vehicle flows, land values and accessibility, bridging the configurational tradition of space syntax with mainstream geographic-information-system 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.