Issue No. 03 - May/June (2005 vol. 25)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2005.71
Alison L. Love , University of California, Santa Cruz
Alex Pang , University of California, Santa Cruz
David L. Kao , NASA Ames Research Center
Ensemble forecasts, outcomes from conditional simulations, or repeated measurements in an experiment all produce multiple instances of the same physical field. This article refers to this as a multivalue data type. Specifically, a multivalue data point contains multiple values for a single variable. If there is a single multivalue data point, then visualizing it can be carried out using a simple graph either showing the different values, or the frequency of the different values. However, if the multivalue data exist over a spatial domain, then the existing suite of visualization techniques has limited power in visualizing them. This article introduces the multivalue data type, and suggests three ways of visualizing spatial multivalue data sets.
uncertainty, distributions, realizations, ensemble forecast, parametric statistics, shape descriptors
D. L. Kao, A. L. Love and A. Pang, "Visualizing Spatial Multivalue Data," in IEEE Computer Graphics and Applications, vol. 25, no. , pp. 69-79, 2005.