There are generally two motivations that cartographers might have for creating a multivariate symbol: either we want to display multiple attributes at the same time to facilitate comparison between distributions, or we want to use multiple visual channels to redundantly represent one attribute for special emphasis. Different combinations of visual variables may better support different map reading tasks (e.g., determining if there is a geographical correlation between two variables or presenting two related variables intended to be read separately). We can turn to psychological research on visual attention to help guide our creation of multivariate symbol sets.
The term visual attention refers to the map user's focusing of his or her gaze and concentration on some particular area of the map. Psychologists have identified two main types of attention that lie on opposite ends of the attention spectrum: selective attention and divided attention. In selective attention, a map user can focus on one visual variable while ignoring another. Visual variable combinations that enable map users to easily read separate data variables are known as separable, whereas visual variable combinations that use divided attention, and are harder to read independently, are known as integral (see Figure 5.cg.13, below). A third, intermediate type of symbol, known as a configural symbol, shows characteristics of being both separable and integral, i.e. it is possible to separate the dimensions of the multivariate symbol, while at the same time it is possible to extract relational information from the symbol (Nelson 2000).
Separable visual variable combinations allow map users to easily compare two places on one or another attribute, but will be more difficult for the map user to determine whether there is some overall relationship between the two variables. In her study, Nelson (2000) found the following visual variable combinations to be separable: hue/shape, hue/size, hue/orientation, value/shape, and value/size. See Figure 5.cg.14 for an example of a map using separable bivariate symbols.
Integral visual variable combinations prevent a map reader from attending to one symbol dimension while ignoring another. Nelson (2000) identified height/width (of rectangular symbols), and color saturation/value as integral. Many other visual variable combinations in Nelson's study (2000) exhibited asymmetrical effects, meaning that one of the visual variables tends to give a stronger visual cue to the reader than the other. For example, the bivariate choropleth map shown in Figure 5.cg.15 uses a hue and value combination to communicate county attributes about population density. Hue is used to communicate three classes of population density in 1990, and value is used to communicate the percent change in population from 1990 to 2000. Between hue and value, hue is the dominant visual variable providing the stronger visual cue, and therefore the reader is better able to separate the differences of hue (and classes of population density) than value (and the change in population density). Other asymmetrical visual variable combinations Nelson (2000) found include hue/pattern and shape/size, with the dominant variable listed first.
Nelson also found that using the same visual variable to represent two variables (e.g., in a segmented point symbol) can produce a configural variable combination that supports cross-variable comparisons. Finally, she found that the combination of value/chroma (or value/saturation) was an integral combination. This finding perhaps provides support for some cartographers' contention that map readers find it difficult to read maps that represent data using color chroma.
Want more examples of maps with multivariate symbols?
- New York Times' Immigration Explorer provides another example of a bivariate choropleth that uses hue and value. In the map shown upon opening the explorer, hue, the qualitative visual variable, communicates the largest foreign-born group (like in Figure 5.cg.14), and value, the quantiative visual variable, communicates the percent of the foreign-born group occupies of the county population.
- This map uses the three primary hues (varied by value) to create a complex trivariate choropleth map communicating relationships between high school graduation, college graduation and median household income.
- Blog post discussing a 1890 map (made in 1894) using texture and numerousness to show race/ethnicity and diversity in New York City sanitary districts.
- Article demonstrating ring maps to depict multiple county attributes in a configural-type multivariate symbol.
Discuss these maps, or other examples you know of, in the Lesson 5 discussion forum in Canvas.
If you are interested in investigating this subject further, I recommend the following:
- Nelson, E.S. 2000. "Designing effective bivariate symbols: the influence of perceptual grouping processes." Cartography and Geographic Information Science. 27(4): 261-78.