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Gravity Model of Migration×Telpiskās mijiedarbības (gravitācijas) modeļi×
NozareHuman GeographyTelpiskā analīze
SaimeRegression modelRegression model
Izcelsmes gads19461971
AutorsGeorge Kingsley Zipf (formalized); analogy to Newton's law of gravitationAlan Wilson (entropy-maximizing family)
TipsSpatial-interaction regression model for migration flowsModel of flows between spatial origins and destinations
PirmavotsZipf, G. K. (1946). The P1 P2 / D hypothesis: On the intercity movement of persons. American Sociological Review, 11(6), 677–686. DOI ↗Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗
Citi nosaukumiMigration Gravity Model, Demographic Gravity Model, Zipf P1P2/D Model, Gravity Model of Spatial Interaction (Migration)gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
Saistītās44
KopsavilkumsThe gravity model of migration explains the volume of movement between two places as proportional to the product of their populations (masses) and inversely proportional to the distance separating them, by direct analogy to Newton's law of universal gravitation. Formalized for intercity movement by George Kingsley Zipf in 1946 and embedded in regional science by Walter Isard, it is the workhorse model of human geography for predicting migration, commuting, and other spatial-interaction flows.Spatial interaction models predict the volume of flows — migrants, commuters, shoppers, trade, trips — between origins and destinations as a function of the size of each place and the distance or cost separating them. By analogy to Newton's gravity, interaction rises with the 'mass' of origin and destination and falls with separation, and Wilson's 1971 entropy-maximizing family put these models on a rigorous footing for transport, migration, and retail analysis.
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ScholarGateSalīdzināt metodes: Gravity Model of Migration · Spatial Interaction Model. Izgūts 2026-06-24 no https://scholargate.app/lv/compare