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Cellular Automata Urban Model×Spatial Microsimulation×
CampoHuman GeographyHuman Geography
FamiliaProcess / pipelineProcess / pipeline
Año de origen19932016
Autor originalRoger White & Guy EngelenDeveloped in the IPF/microsimulation tradition; synthesized for geography by Lovelace & Dumont
TipoSpatially explicit simulation of urban land-use change on a cell gridMethod for generating and analysing synthetic individual-level populations within small areas
Fuente seminalWhite, R., & Engelen, G. (1993). Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A, 25(8), 1175–1199. DOI ↗Lovelace, R., & Dumont, M. (2016). Spatial Microsimulation with R. Chapman and Hall/CRC, Boca Raton. ISBN: 9781498711548
AliasUrban Cellular Automata, CA Urban Growth Model, Constrained Cellular Automata, White-Engelen CA ModelSmall-Area Population Synthesis, Synthetic Population Generation, Geographical Microsimulation, Spatial Microdata Estimation
Relacionados44
ResumenA cellular automata (CA) urban model simulates the growth and transformation of cities by dividing space into a grid of cells, each holding a land-use state, and letting those states evolve through local transition rules that depend on the states of neighbouring cells. Introduced for urban form by Roger White and Guy Engelen in 1993 and popularized in Michael Batty's work on cities as complex systems, the approach reproduces realistic, fractal urban patterns from simple bottom-up rules rather than top-down equations. It has become a workhorse for exploring how compact or sprawling settlement patterns emerge from neighbourhood-scale interactions under regional land demand.Spatial microsimulation is a family of techniques for generating realistic synthetic populations of individuals within small geographic areas, by combining detailed but geographically coarse survey microdata with geographically fine but aggregate census tables. It estimates, for every neighbourhood, a population of individuals whose collective characteristics match the published margins — the right number of each age, sex, income, and tenure group — even though no survey directly samples individuals at that fine scale. Synthesized for the geographic community in Robin Lovelace and Morgane Dumont's 2016 book, it bridges the gap between rich individual data and small-area aggregates so that policy and behaviour can be modelled where people actually live.
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ScholarGateComparar métodos: Cellular Automata Urban Model · Spatial Microsimulation. Recuperado el 2026-06-24 de https://scholargate.app/es/compare