Computer Graphics and Visual Computing (CGVC) 2018

pp. 163 - 171

When Size Matters: Towards Evaluating Perceivability of Choropleths

Liam McNabb, Robert S. Laramee, and Max Wilson


Choropleth maps are an invaluable visualization type for mapping geo-spatial data. One advantage to a choropleth map over other geospatial visualizations such as cartograms is the familiarity of a non-distorted landmass. However, this causes challenges when an area becomes too small in order to accurately perceive the underlying color. When does size matter in a choropleth map? We conduct an experiment to verify the relationship between choropleth maps, their underlying color map, and a user's perceivability. We do this by testing a user's perception of color relative to an administrative area's size within a choropleth map, as well as user-preference of fixed-locale maps with enforced minimum areas. Based on this initial experiment we can make the first recommendations with respect to a unit area's minimum size in order to be perceivably useful.

CCS Concepts: Human-centered computing --> User studies; Geographic visualization; Information visualization; Computing methodologies --> Visibility; Perception



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