Krahasoni metodat

	Urban Network Analysis	Street Network Analysis
Fusha	Urban Studies	Urban Studies
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	2012	2017
Krijuesi	Andres Sevtsuk & Michael Mekonnen	Geoff Boeing (OSMnx); graph-theoretic street analysis tradition
Lloji	Graph-based centrality analysis of spatial urban networks	Graph-theoretic measurement of street-network structure and connectivity
Burimi themelues	Sevtsuk, A., & Mekonnen, M. (2012). Urban network analysis: A new toolbox for ArcGIS. Revue Internationale de Géomatique, 22(2), 287–305.	Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139.
Emërtime të tjera	UNA Toolbox, Spatial Network Centrality, Building-Level Network Analysis, Street Network Centrality Analysis	Street Pattern Analysis, Road Network Metrics, Urban Street Connectivity Analysis, Configurational Street Analysis
Të lidhura	4	4
Përmbledhja	Urban network analysis treats a city as a spatial graph of streets and buildings and measures the centrality of each location — how reachable, how central, and how well-connected it is along the actual travel network. Formalized in the Urban Network Analysis toolbox by Andres Sevtsuk and Michael Mekonnen in 2012, it differs from generic network science by weighting graph nodes with real urban data such as building floor area or population and by computing centralities within bounded search radii. The result is a set of metrics — reach, gravity, betweenness, closeness, straightness — that quantify the structural role of every building or street segment in the urban fabric.	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.