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Krigage universel (Krigage avec une tendance)×Cokrigage×Pondération par distance inverse (IDW)×
DomaineAnalyse spatialeAnalyse spatialeAnalyse spatiale
FamilleRegression modelRegression modelRegression model
Année d'origine196919631968
Auteur d'origineGeorges MatheronGeorges Matheron (geostatistics); multivariate extensionDonald Shepard
TypeGeostatistical interpolation with spatial trendMultivariate geostatistical interpolationDeterministic spatial interpolation
Source fondatriceMatheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 23rd ACM National Conference, 517–524. DOI ↗
Aliaskriging with a trend, kriging with drift, trend kriging, evrensel krigingco-kriging, multivariate kriging, ortak krigingIDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyon
Apparentées333
RésuméUniversal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances.Cokriging extends kriging to use one or more correlated secondary variables to improve prediction of a primary variable. When the variable of interest is sparsely sampled but a related, cheaper-to-measure variable is densely sampled, cokriging borrows strength from the secondary variable through their cross-correlation, yielding more accurate interpolations and prediction variances than kriging the primary variable alone.Inverse distance weighting is a simple, deterministic method for estimating values at unsampled locations by taking a weighted average of nearby measured points, where closer points carry more weight. Introduced by Donald Shepard in 1968, it embodies the first law of geography — near things are more related than distant things — and is one of the most widely used interpolation methods in GIS for mapping continuous fields such as rainfall, elevation, or pollution from scattered samples.
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ScholarGateComparer des méthodes: Universal Kriging · Cokriging · Inverse Distance Weighting. Consulté le 2026-06-20 sur https://scholargate.app/fr/compare