Interactive visualization of uncertain spatial and spatio-temporal data under different scenarios: an air quality example

Authors:
Edzer J. Pebesma;Kor de Jong;David Briggs
Affiliations:
Faculty of Geosciences, Utrecht University, The Netherlands;Faculty of Geosciences, Utrecht University, The Netherlands;Imperial College, London, UK
Venue:
International Journal of Geographical Information Science - Special Issue in Honour of the Contribution of Peter Burrough to Geographical Information Science
Year:
2007

Citing 5
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Abstract

This paper introduces a method for visually exploring spatio-temporal data or predictions that come as probability density functions, e.g. output of statistical models or Monte Carlo simulations, under different scenarios. For a given moment in time, we can explore the probability dimension by looking at maps with cumulative or exceedance probability while varying the attribute level that is exceeded, or by looking at maps with quantiles while varying the probability value. Scenario comparison is done by arranging the maps in a lattice with each panel reacting identically to legend modification, zooming, panning, or map querying. The method is illustrated by comparing different modelling scenarios for yearly NO2 levels in 2001 across the European Union.