Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Krigage Universel Local× | Krigage ordinaire local× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1969/1997 | 1970s–1990s |
| Auteur d'origine≠ | Matheron, G. (trend/drift kriging); local neighborhood approach standard in geostatistical practice | Journel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner |
| Type≠ | Spatial interpolation model | Geostatistical interpolation (local/moving-window variant) |
| Source fondatrice≠ | Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press. ISBN: 9780195115383 | Chiles, J.-P., & Delfiner, P. (1999). Geostatistics: Modeling Spatial Uncertainty. Wiley. ISBN: 978-0471083153 |
| Alias | local UK, local kriging with trend, local KED, local kriging with external drift | moving window kriging, local kriging, neighborhood kriging, LOK |
| Apparentées | 5 | 5 |
| Résumé≠ | Local Universal Kriging is a geostatistical interpolation method that combines a spatially varying deterministic trend with a stochastic residual, estimated using only nearby observations within a defined search neighborhood. It generalizes local ordinary kriging by explicitly modeling and removing a polynomial or covariate-driven drift before interpolating the residual surface. | Local Ordinary Kriging (LOK) is a geostatistical interpolation method that estimates values at unsampled locations using only a spatially defined moving neighborhood of nearby observations. By restricting each prediction to a local data window rather than the full dataset, LOK accommodates spatial non-stationarity, reduces computational cost, and often yields more accurate local predictions than global ordinary kriging. |
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