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Co-krigage : interpolation géostatistique multivariée×Régression Pondérée Géographiquement (GWR)×
DomaineAnalyse spatialeAnalyse spatiale
FamilleRegression modelRegression model
Année d'origine1965-19782002
Auteur d'origineMatheron, G.; extended by Journel & HuijbregtsFotheringham, Brunsdon & Charlton
TypeGeostatistical interpolationLocal spatial regression
Source fondatriceJournel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Aliascokriging, co-regionalization kriging, multivariate kriging, CKGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Apparentées55
RésuméCo-kriging is a geostatistical interpolation technique that predicts the spatial distribution of a primary variable by leveraging its spatial cross-correlation with one or more secondary (co-) variables. It extends ordinary kriging to multivariate settings, yielding more accurate predictions when the secondary variable is more densely sampled or spatially correlated with the primary variable of interest.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
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ScholarGateComparer des méthodes: Co-kriging · Geographically Weighted Regression. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare