Environmental data is nearly always multivariate and often spatial–temporal. Thus to interpolate the data in space or to predict in space–time it is necessary to use a multivariate spatial–temporal method. Cokriging is easily extended to spatial–temporal data if there are valid space–time variograms or covariance functions. Various authors have proposed such models. In this paper, a generalized product–sum model is used with a linear coregionalization model for cokriging. The GSLib “COKB3D” program was modified to incorporate the space–time linear coregionalization model (ST-LCM), using the generalized product–sum variogram model. Hence, a new GSLib software, named “COK2ST”, is proposed. To demonstrate the use of the software, hourly measurements of carbon monoxide and nitrogen dioxide from the Puglia region in Italy are used.
FORTRAN programs for space-time multivariate modeling and prediction
DE IACO, Sandra;PALMA, Monica;POSA, Donato
2010-01-01
Abstract
Environmental data is nearly always multivariate and often spatial–temporal. Thus to interpolate the data in space or to predict in space–time it is necessary to use a multivariate spatial–temporal method. Cokriging is easily extended to spatial–temporal data if there are valid space–time variograms or covariance functions. Various authors have proposed such models. In this paper, a generalized product–sum model is used with a linear coregionalization model for cokriging. The GSLib “COKB3D” program was modified to incorporate the space–time linear coregionalization model (ST-LCM), using the generalized product–sum variogram model. Hence, a new GSLib software, named “COK2ST”, is proposed. To demonstrate the use of the software, hourly measurements of carbon monoxide and nitrogen dioxide from the Puglia region in Italy are used.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
