Σύγκριση μεθόδων

	Ordinary Kriging	Χωρική Αυτοσυσχέτιση
Πεδίο	Χωρική Ανάλυση	Χωρική Ανάλυση
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1963	1950
Δημιουργός	Georges Matheron (formalising D.G. Krige's empirical work)	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Τύπος	Geostatistical interpolation	Spatial statistic / exploratory spatial data analysis
Θεμελιώδης πηγή	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266.	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.
Εναλλακτικές ονομασίες	OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Συναφείς	4	5
Σύνοψη	Ordinary Kriging (OK) is the standard geostatistical method for interpolating a continuous spatial variable at unsampled locations. It derives optimal, unbiased weights from the spatial covariance structure of the data, making it the Best Linear Unbiased Predictor (BLUP) under stationarity assumptions. Unlike simpler distance-based methods, it also provides a prediction uncertainty (kriging variance) 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.