Thematic Maps: Visualizing Data

We first introduced thematic maps in Lesson 1, and described them as maps intended to highlight features, data, or concepts (either quantitative or qualitative). In assignments 1 and 2, we used visual variables to show order and category of typical map features. In assignments 3 and 4, we introduced the use of projections and symbolized methods for terrain visualization.

The maps we’ve created so far have visualized fairly tangible information—we have indeed been creating abstract representations of the real world, with roads, rivers, lakes, county lines, etc., with hues and shapes different from what would be captured by a photograph. We have also visualized the concept of travel routes, be they on foot or by plane. But on balance, our designs have more or less matched a physical phenomenon or object. So, in this lesson, we turn to more abstract depictions of the world, designed using thematic, statistical data. View for example, the map in Figure 6.1.1.

Figure 6.1.1: A county-level map of unemployment.

Credit: Cary Anderson© Penn State is licensed under CC BY-NC-SA 4.0.
Data Sources: Esri, US Census Bureau

This map uses color value—not to show category or hierarchy of map features—but to visually encode county- level quantitative unemployment data. Figure 6.1.1 also simplifies the map of the US (not showing even major highways or mountain ranges, but only state and county boundaries) to emphasize the map’s theme.

Due to thoughtful use of color and a simple layout design, this map successfully communicates geographic trends of unemployment across the United States. Was this the best design and symbolization choice to show this geographic distribution? Is there a better way?

View the map in Figure 6.1.2.

Figure 6.1.2: A proportional symbol map of population.

Credit: Cary Anderson© Penn State is licensed under CC BY-NC-SA 4.0.
Data Source: Esri, The National Map

This map uses a similar color scheme and layout, but encodes its data (this time population rather than unemployment) primarily using proportionally-sized symbols. Color value is used for additional effect, a technique called dual encoding.

Both of these maps (6.1.1; 6.1.2) employ appropriate cartographic conventions (e.g., assigning lighter color values to lower data values and darker color values to higher data values). But there are other conventions that this cartographer could have used with each dataset that would have been equally appropriate (e.g., using a diverging color scheme for Figure 6.1.1 and a single hue fill for Figure 6.1.2). There are also other symbolization methods that they could have used that would have been—arguably—not meeting the map purpose. How do you decide?

Before beginning the how of making a map, we need to take a step back and consider the what—the geographic phenomena we want our map to be about.

Geographic phenomena are elements that exist over geographic space. When we say geographic, we typically mean anything tangible that is associated with Earth. On the other hand, spatial refers to connections that exist in space (broadly defined). So, while still spatial and can be mapped, the connections between the neurons in your brain or the arrangement of atoms in a ceramic material are generally not referred to as “geographic" phenomena. In this lesson, you will learn tools for conceptualizing, visualizing, and communicating the many geographic phenomena that do.