Multivariate Maps

Multivariate Maps

So far in this course, we have discussed many different ways of symbolizing data using visual variables. Our focus has been primarily on univariate maps—maps that show only one thematic data variable.

There are many cases where mapping a single variable is needed. More complex data and purposes often require mapping a number of different variables at once. This is called multivariate mapping. The term multivariate map is typically defined as a map that displays two or more variables at once (Field 2018). Note however, that bivariate mapping (mapping only two variables is distinct). When creating multivariate maps, you will think about the best way to symbolize each variable, as well as how they can be combined to suit your map's audience, medium, and purpose. 

Figure 7.1.1: A map of Section 8 housing and rent prices in Portland, Oregon.

Credit: Oregon Metro Council(link is external)

Figure 7.1.1 shows a multivariate map. The map visualizes two variables at each location: rent prices and the number of Section 8 vouchers. These variables are individually symbolized appropriately. First, rental prices are visually encoded with a sequential color scheme—a good symbolization choice for normalized data such as rates. Second, the number of Section 8 vouchers at each location is visualized by adjusting symbol size—an appropriate visual variable for mapping count data. Together, these symbols work to visualize this housing data from Portland.

Note that the legend in Figure 7.1.1 is more complicated than many of the legends that we’ve seen so far. The format shown—one variable along the x-axis, and one along the y-axis, is common in bivariate maps, or maps that display two variables. Doing so not only explains how to data is visually encoded, but helps the map reader understand how the data are related to each other. The more visually complicated a map becomes, the more challenging it will be to design a useful legend. However, your legend is central to the reader accurately interpretating your map, so don’t treat legend design as an afterthought. The map in Figure 7.1.2 below uses short text blurbs to assist the reader in this interpretation.

Figure 7.1.2: A multivariate map about the AIDS epidemic in Africa.

Credit: US Census Bureau(link is external)

As we continue through this lesson, keep an eye on the legend designs. Some maps, such as bivariate choropleth maps, have a more standardized legend designs. Others, such as what appears in Figure 7.1.2, are somewhat less conventional; they are designed and customized by the cartographer to suit the map’s data and purpose. Legend design is an important component of cartographic design in general, but is particularly important for multivariate maps.