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Pondération par distance inverse (IDW)×Cokrigage×
DomaineAnalyse spatialeAnalyse spatiale
FamilleRegression modelRegression model
Année d'origine19681963
Auteur d'origineDonald ShepardGeorges Matheron (geostatistics); multivariate extension
TypeDeterministic spatial interpolationMultivariate geostatistical interpolation
Source fondatriceShepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 23rd ACM National Conference, 517–524. DOI ↗Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗
AliasIDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyonco-kriging, multivariate kriging, ortak kriging
Apparentées33
RésuméInverse 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.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.
ScholarGateJeu de données
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  2. 2 Sources
  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Inverse Distance Weighting · Cokriging. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare