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Spatial Microsimulation×Geodemographic Classification×
분야Human GeographyHuman Geography
계열Process / pipelineProcess / pipeline
기원 연도20162005
창시자Developed in the IPF/microsimulation tradition; synthesized for geography by Lovelace & DumontRichard Webber (and the geodemographics tradition synthesized by Harris, Sleight & Webber)
유형Method for generating and analysing synthetic individual-level populations within small areasPipeline that clusters small areas into interpretable neighbourhood types
원전Lovelace, R., & Dumont, M. (2016). Spatial Microsimulation with R. Chapman and Hall/CRC, Boca Raton. ISBN: 9781498711548Harris, R., Sleight, P., & Webber, R. (2005). Geodemographics, GIS and Neighbourhood Targeting. John Wiley & Sons, Chichester. ISBN: 9780470864135
별칭Small-Area Population Synthesis, Synthetic Population Generation, Geographical Microsimulation, Spatial Microdata EstimationNeighbourhood Classification, Area Classification, Geodemographic Segmentation, Neighbourhood Typology
관련44
요약Spatial 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.Geodemographic classification is the process of grouping small geographic areas into a set of distinctive neighbourhood types according to the demographic, socioeconomic, and housing characteristics of the people who live there. It rests on the principle that 'birds of a feather flock together' — that residents of a neighbourhood tend to resemble one another and differ from those elsewhere — and turns dozens of census variables into a single, interpretable label for every area. Commercial systems such as Mosaic and ACORN and open classifications such as the UK Output Area Classification are all built this way, and the approach was consolidated as a discipline by Harris, Sleight and Webber in 2005.
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ScholarGate방법 비교: Spatial Microsimulation · Geodemographic Classification. 2026-06-24에 다음에서 검색함: https://scholargate.app/ko/compare