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분야공간분석공간분석
계열Regression modelRegression model
기원 연도19991969
창시자Cressie & Huang; Kyriakidis & JournelGeorges Matheron
유형Geostatistical interpolationGeostatistical interpolation with spatial trend
원전Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340. DOI ↗Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗
별칭spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-timekriging with a trend, kriging with drift, trend kriging, evrensel kriging
관련43
요약Space-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.Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances.
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