Multivariate Choropleths

Multivariate Choropleths

As choropleth maps are the most popular type of univariate thematic map, it is not surprising that they are also commonly used in multivariate mapping. Bivariate choropleth maps visualize two variables. Note that while cartographers have historically described maps of two data variables as bivariate, these maps can also be described as multivariate (more than one variable). In the context of this lesson and course, we will generally use the more comprehensive description multivariate maps.

The map in Figure 7.2.1 is an example of a bivariate (or multivariate) choropleth map from a research article on COVID-19 and population movement. Examine the legend. Note that a hue progression (purple to yellow – vertically on the legend) has been applied to visually encode population vulnerability. Color lightness (horizontally on the legend) to visually encode population movement, or “stay-at-home behavior.” The legend text explains the logic behind the ordering of the color chips in ther 3x3 diamond legend in the lower right of the map.

Figure 7.2.1: County-level bivariate map comparing overall 2018 CDC Social Vulnerability Index (SVI) to median stay-at-home behavior (April 7–20, 2020), United States.

Credit: Annals of Epidemiology Volume 64, December 2021, Pages 76-82(link is external). Licence: CC BY 4.0

Using color hue to encode population vulnerability is a sequential quantitative variable—a design choice we have discouraged in previous lessons. In general, color lightness is a much better choice for encoding quantitative data. In this map, however, color lightness is already being used to map the other variable—population movement (stay-at-hoome behavior). Creating multivariate maps sometimes requires bending the rules of cartographic conventions a bit so as to best represent all of your data.