Dynamic graphics for exploring spatial dependence in multivariate spatial data
Through exploratory spatial data analysis of geostatistical data, one looks to identify (spatial) outliers and pockets of nonstationarity; spatial trend; and spatial dependence inherent in the data set. In this paper, we propose a dynamic graphical environment for the exploration of spatial data with emphasis on the characterization of spatial dependence. The identity of individual data points has been maintained in the graphics. This allows extreme or outlying points to be identified and investigated further; and, in contrast to more aggregated graphical summaries, it allows interesting patterns to be explored that might otherwise be obscured. Traditional spatial dependence plots are enhanced with dynamic graphical tools. Both univariate and multivariate spatial data are considered and a bivariate spatial data set, from a study of surface-water contamination, is used to illustrate the graphical tools. 1997 OPA (Overseas Publishers Association) Amsterdam B.V. Published in The Netherlands under license by Gordon and Breach Science Publishers.
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