手法を比較

	Ordinary Kriging	空間的自己相関
分野	空間分析	空間分析
系統	Regression model	Regression model
提唱年	1963	1950
提唱者	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)
種類	Geostatistical interpolation	Spatial statistic / exploratory spatial data analysis
原典	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.
別名	OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
関連	4	5
概要	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.