At its simplest level of representation, spatial data exists as points, lines, areas, or rasters. But representing these features, combined with their attributes, often means encoding something more complex than just geographic location. Symbolization encodes both the where and what components of features. It reflects the interplay between the feature dimension, whether you need to show single or multiple instances, and the level of measurement you need to describe. Symbolization can show difference (nominal), rank (ordinal), or some numeric measurement (interval or ratio). Symbolization can take on a range of functions on a map but should be clear, concise, and easily understood by anyone reading your map. In many ways, symbolization can be regarded as the coding of map features to communicate meaning.
The following table shows a range of ways you can modify feature symbolization to give it different meaning. The diagram references visual variables, which are ways you can alter symbols to support the intended message. Variations in symbol shape imply qualitative difference. Variations in symbol size imply quantitative difference. For instance, to show the locations of different types of point features, you might vary the shape of the point symbol based on the attribute that defines the type. Alternatively, to show how an attribute varies in magnitude at those points, you might vary the size of the symbols. These visual variables are based on a long history of cartographic communication. Follow these guidelines to best match symbol characteristics to the quantitative and qualitative properties of features.
| Visual variable | Point | Linear | Areal | 2.5D | True 3D |
|---|---|---|---|---|---|
Spacing |  |  |  |  |  |
Size |  |  |  |  |  |
Perspective height |  |  |  |  | Not possible |
Orientation |  |  |  | Not recommended |  |
Shape |  |  |  | Not recommended |  |
Arrangement |  |  |  | Not recommended |  |
Value |  |  |  |  |  |
Hue |  |  |  |  |  |
Lightness |  |  |  |  |  |
Saturation |  |  |  |  |  |
Show qualitative and quantitative differences
Making sensible choices about how to represent your features to convey just the right message is key to making your map communicate effectively. For instance, if you want to show how cities (represented by point symbols) differ in their population size you would probably choose to change the size of the symbol used to represent the points. Larger symbols represent larger magnitudes and this is how our eyes and brains process the meaning of a large symbol compared to a smaller one. In another example, if you wanted to show the difference between a railroad and a freeway, changing the size (thickness) of the line isn't going to immediately show that difference. Instead, you would probably change the shape of the line to show a difference between the two features.
Assigning meaning to symbols generally means deciding whether you're showing a quantitative or a qualitative difference, that is, a difference in size or type. The following table gives some advice on the recommended ways in which you should modify your features depending on feature type and what you are trying to show. Some methods are preferable to others.
| Qualitative | Quantitative | |
|---|---|---|
Point | Preferred: hue, shape Less preferred: orientation, arrangement | Preferred: size, value, lightness Less preferred: perspective height, size |
Line | Preferred: hue, shape Less preferred: arrangement | Preferred: size, spacing Less preferred: perspective height, value, lightness |
Area | Preferred: hue, shape Less preferred: orientation, arrangement | Preferred: value, lightness, saturation, size Less preferred: perspective height, hue |
2.5D | None recommended | Preferred: perspective height, lightness, value Less preferred: saturation |
3D | Preferred: orientation, arrangement, shape Less preferred: hue | Preferred: lightness, value, saturation Less preferred: size, spacing |