An Evaluation of Visualization Methods for Population Statistics Based on Choropleth Maps
This addresses visualization challenges for researchers and policymakers using population data, but it is incremental as it builds on existing map techniques.
The paper evaluates augmentations to choropleth maps for conveying population statistics, finding that 3D choropleth maps show potential while standard maps have low accuracy with multivariate data, and introduces popcharts for fine-scale density visualization.
We evaluate several augmentations to the choropleth map to convey additional information, including glyphs, 3D, cartograms, juxtaposed maps, and shading methods. While choropleth maps are a common method used to represent societal data, with multivariate data they can impede as much as improve understanding. In particular large, low population density regions often dominate the map and can mislead the viewer as to the message conveyed. Our results highlight the potential of 3D choropleth maps as well as the low accuracy of choropleth map tasks with multivariate data. We also introduce and evaluate popcharts, four techniques designed to show the density of population at a very fine scale on top of choropleth maps. All the data, results, and scripts are available from https://osf.io/8rxwg/.