A comparison of hybrid maps for the visualization of two geolocated quantitative variables

Abstract

Thematic maps, like choropleth maps, symbol maps or cartograms, are commonly used to visualize spatial quantitative data. Many studies have been conducted to compare the different approaches and thus define the best strategies to produce suitable and efficient maps. When analyzing spatial data, it is also often necessary to visualize and compare several variables on the same map. Therefore, the question arises of how to best associate two variables in a single representation without one of them prevailing over the other, while avoiding overloading the map and making it difficult to interpret. In this article, we propose a comparison of five types of bivariate maps based on a user study. Participants performed a set of tasks using different maps produced from multiple datasets. Our analysis is based on three approaches: (1) quantitative analysis of user answer accuracy, (2) quantitative analysis of user answer times, and (3) quantitative and qualitative analysis of user feedback. The results suggest that combining symbol and choropleth maps is the most effective approach among those tested, while combining cartograms with any technique is the worst.