Visualization of Multivariate Geographic Data
Problem
Datasets often have geographically distributed variables, and many of them (e.g., dozens). Variables are also often measured at specific locations (instead of areas like, e.g., political districts). Examples include air quality sensors or geochemical surveys.
To show such data, visualization approaches often choose multivariate glyphs or small multiples (of symbol maps, heatmaps, ...). Each have their own set of drawbacks. Multivariate glyphs suffer, as all symbol maps, eventually from overplotting/occlusion. Small multiples not glyphs do not scale all too well to 20+ variables due to limited screen sizes. Scale (e.g., patterns visible when looking at few square km vs patterns visible when looking at whole map) is rarely considered in either.
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