FORTRAN programs for space-time multivariate modeling and prediction

  • Authors:

  • S. De Iaco;D. E. Myers;M. Palma;D. Posa

  • Affiliations:

  • Universití del Salento, Facoltí di Economia, Dip.to di Scienze Economiche e Matematico-Statistiche, Complesso Ecotekne, Via per Monteroni, 73100 Lecce, Italy;University of Arizona, Department of Mathematics, Tucson, AZ, USA;Universití del Salento, Facoltí di Economia, Dip.to di Scienze Economiche e Matematico-Statistiche, Complesso Ecotekne, Via per Monteroni, 73100 Lecce, Italy;Universití del Salento, Facoltí di Economia, Dip.to di Scienze Economiche e Matematico-Statistiche, Complesso Ecotekne, Via per Monteroni, 73100 Lecce, Italy

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2010

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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.