visual variables
Most students of cartography will encounter a figure that shows visual variables and a list of things with opaque names (selective, associative, ordered, quantitative) that each variable is good at doing.
credit: Axis Maps
At first glance, the chart seems pretty straightforward. It appears to list the different kinds of visual things that we can use to symbolize geographic data. It suggests that there are a small number, maybe seven, kinds of symbols that we can then vary in ways that allow us to show differences and similarities across the data.
Many students recognize this and move on, in part because the list of things under each column are much more difficult to understand quickly. They are based on a theory of perception by Jacques Bertin and presented in his seminal book Semiology of Graphics. Understanding Bertin’s theory will help you know how to help readers perceive groups, sub-groups, hierarchy, and ratios in your maps. Bertin’s theory provides reasons for why some design decisions regarding the presentation of indexes are better than others.
associative variables
Use associative variables to help the map reader see a set of elements as a single group.
Associative perception means our eyes can see a set of elements as a group even though the variable may differ. For example, the image below shows a grid of locations symbolized with different shapes. All the elements in the array use the shape variable, but the shape itself varies across the array. Despite this variation, we can perceive the whole array as a group, because shape is associative. Most people can perceive a collection of symbols with different shapes as a group because shape supports associative perception.
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In contrast, the image below shows an array of locations symbolized with the value variable. The value varies across each location. Can you easily perceive the entire array of symbols as a group? When I look at it, I see more of a left-side group and a right-side group and I can’t quite see where one ends and the other starts. Most people find it very difficult to perceive a set of symbols with different values as a single group because value does not support associative perception.
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The key idea is that associative perception means we can ignore differences with in variable that allows us to see a larger group. For this reason, associative variables are helpful in cartography for representing thematic categories of geographic features.
selective variables
Use selective variables to help the map reader see subsets of elements within a larger group.
Selective perception means our eyes can see a set of elements as a subgroup because of differences in the visual variable. For example, the image belows shows a map of points that use three different hues. In this case, all the symbols use the same type of visual variable (hue), they simply differ in the kind of hue shown.
Can you perceive each kind of hue as a distinct subgroup and isolate it from the other symbols in your mind’s eye? Most people can do this, because hue supports selective perception.
Now look at the figure below. It shows a set of elements with the shape variable, where the shape itself differs across the set. Can you perceive each kind of shape as a distinct subgroup and isolate it from the other symbols in your mind’s eye? Most people find this very difficult. It is much easier to mechanically separate the different shapes in small multiples to see the subgroups. This is because shape does not support selective perception..
The key idea is that selective perception means that most people will be able to see sub-groups from a larger group. For this reason, selective variables are helpful in cartography for representing parts-of relationships (distinct islands of an archipelago) and kind-of relationships (deciduous vs coniferous subgroups of larger forest class).
ordinal variables
Use ordinal variables to help the map reader see ranked levels and hierarchy in elements of a group.
quantiative
Use size to help the reader difference in the ratios of two or more signs.
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