Abstract
Many geospatial science subdisciplines analyze variables that vary over both space and time. The space–time autoregressive (STAR) model is one specification formulated to describe such data. This paper summarizes STAR specifications that parallel geostatistical model specifications commonly used to describe space–time variation, with the goal of establishing synergies between these two modeling approaches. Resulting expressions for space–time correlograms derived from 1st-order STAR models are solved numerically, and then linked to appropriate space–time semivariogram models.
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Griffith, D.A., Heuvelink, G.B.M. (2012). Deriving Space-Time Variograms from Space-Time Autoregressive (STAR) Model Specifications. In: Yeh, A., Shi, W., Leung, Y., Zhou, C. (eds) Advances in Spatial Data Handling and GIS. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25926-5_1
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DOI: https://doi.org/10.1007/978-3-642-25926-5_1
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