השוואת שיטות

	קריגינג מרחב-זמן	קריגינג רגיל
תחום	ניתוח מרחבי	ניתוח מרחבי
משפחה	Regression model	Regression model
שנת המקור	1999	1963
הוגה השיטה	Cressie & Huang; Kyriakidis & Journel	Georges Matheron (formalising D.G. Krige's empirical work)
סוג	Geostatistical interpolation	Geostatistical interpolation
מקור מכונן	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266.
כינויים	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time	OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor
קשורות	4	4
תקציר	Space-Time Kriging is a geostatistical interpolation method that predicts an unknown variable at any location and time by borrowing strength from nearby observations in both space and time simultaneously. It models the joint spatial-temporal covariance structure through a space-time variogram, then uses optimal linear weights to produce predictions with quantified uncertainty.	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.