ScholarGate
Asistent

Uporedite metode

Pregledajte izabrane metode jednu pored druge; redovi koji se razlikuju su istaknuti.

Urban Scaling Laws×Urban Network Analysis×
OblastUrban StudiesUrban Studies
PorodicaRegression modelProcess / pipeline
Godina nastanka20072012
TvoracLuís Bettencourt & Geoffrey WestAndres Sevtsuk & Michael Mekonnen
TipPower-law regression of urban indicators against population sizeGraph-based centrality analysis of spatial urban networks
Temeljni izvorBettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences, 104(17), 7301–7306. DOI ↗Sevtsuk, A., & Mekonnen, M. (2012). Urban network analysis: A new toolbox for ArcGIS. Revue Internationale de Géomatique, 22(2), 287–305. DOI ↗
Drugi naziviUrban Scaling, Settlement Scaling Theory, Power-Law Urban Scaling, Superlinear and Sublinear Urban ScalingUNA Toolbox, Spatial Network Centrality, Building-Level Network Analysis, Street Network Centrality Analysis
Srodne44
SažetakUrban scaling laws describe how the aggregate properties of cities — wealth, innovation, infrastructure, crime — change systematically with population size, following power laws rather than growing in simple proportion. Building on the 2007 work of Luís Bettencourt, Geoffrey West and colleagues, the framework shows that socioeconomic outputs typically scale superlinearly (a doubling of population more than doubles GDP and patents) while infrastructure scales sublinearly (larger cities need proportionally fewer roads and cables per person), with a single exponent β capturing the regularity across an entire urban system.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.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 1 Izvori
  3. PUBLISHED

Idi na pretragu Preuzmi slajdove

ScholarGateUporedite metode: Urban Scaling Laws · Urban Network Analysis. Preuzeto 2026-06-25 sa https://scholargate.app/sr/compare