Comparer des méthodes

	Krigeage ordinaire global	Autocorrélation spatiale
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1951–1963	1950
Auteur d'origine	Danie G. Krige; formalized by Georges Matheron	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Type	Geostatistical interpolation	Spatial statistic / exploratory spatial data analysis
Source fondatrice	Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley. ISBN: 978-0471002550	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.
Alias	ordinary kriging, OK, global kriging, stationary ordinary kriging	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Apparentées	5	5
Résumé	Global Ordinary Kriging (GOK) is the canonical geostatistical interpolation method that estimates values at unsampled locations as a weighted linear combination of nearby observations. It fits a single variogram model to the entire dataset, enforcing a global stationarity assumption, and produces optimal unbiased predictions along with quantified prediction uncertainty at every interpolated point.	Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.