手法を比較

	空間時間クリギング	時空間的空間自己相関
分野	空間分析	空間分析
系統	Regression model	Regression model
提唱年	1999	1981–1992
提唱者	Cressie & Huang; Kyriakidis & Journel	Cliff & Ord; extended by Anselin and others
種類	Geostatistical interpolation	Spatial autocorrelation statistic
原典	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.	Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134.
別名	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time	STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence
関連	4	5
概要	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.	Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss.