Edzer J. Pebesma and Derek Karssenberg and Kor de Jong.
Dynamic Visualisation of Spatial and Spatio-Temporal Probability Distribution Functions.
In M. Caetano and M. Painho (Eds.), 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences., pp. 825--831, 2006.

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Abstract:

In this paper we will present and demonstrate aguila, a tool for interactive dynamic visual analysis of gridded data that come as spatial or spatio-temporal probability distribution functions. Probability distribution functions are analysed in their cumulative form, and we can choose to visualize exceedance probabilities given a threshold value, or its inverse, the quantile values. Threshold value or quantile level can be modified dynamically. In addition, classified probabilities in terms of (1-alpha)x100% (e.g. 95%) confidence or prediction intervals can be visualized for a given threshold value. Different modelling scenarios can be compared by organizing maps in a regular lattice, where individual maps (scenarios) are shown in panels that share a common legend and behave identically to actions like zooming, panning, and identifying (querying) cells. Variability over time is incorporated by showing sets of maps as animated movies. We will demonstrate this tool using sea floor sediment quality predictions under different spatial aggregation scenarios (block sizes), covering the Dutch part of the North Sea. The tool is freely available in binary and source code form; source code is distributed under the Gnu GPL; grid maps are read from disc through the GDAL library, or from memory as e.g. in an R session.

Bibtex:

@InProceedings{  pebesma:2006:VPDF,
  author = 	 {Edzer J. Pebesma and Derek Karssenberg and Kor de Jong},
  title = 	 {Dynamic Visualisation of Spatial and Spatio-Temporal Probability Distribution Functions},
  booktitle = {7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences.},
  pages = 	 {825--831},
  year = 	 {2006},
  editor = 	 {M. Caetano and M. Painho},
}

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References:

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Pebesma, E.J., R.N.M. Duin (2005). Spatio-temporal mapping of sea floor sediment pollution in the North Sea. In: Ph. Renard, and R. Froidevaux, eds. Proceedings GeoENV 2004 - Fifth European Conference on Geostatistics for Environmental Applications; Springer.
Pebesma, E.J., K. de Jong, D. Briggs (accepted). Interactive visualization of uncertain spatial and spatio- temporal data under different scenarios: an air quality example. Int.J. of GIS, accepted for publication.