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Pondération par distance inverse (IDW)×Krigage universel (Krigage avec une tendance)×
DomaineAnalyse spatialeAnalyse spatiale
FamilleRegression modelRegression model
Année d'origine19681969
Auteur d'origineDonald ShepardGeorges Matheron
TypeDeterministic spatial interpolationGeostatistical interpolation with spatial trend
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 enterpolasyonkriging with a trend, kriging with drift, trend kriging, evrensel 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.Universal 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.
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  1. v1
  2. 2 Sources
  3. PUBLISHED

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