PrintSpecifying Colors
When you hear the word "color," words such as blue, red, and green likely spring to mind. Though these are colors in the colloquial sense, these are better described as color hues. Color has more dimensionality than just the color name. In fact, when thinking about color as a visual variable, each color is specified not just by hue but by three dimensions: hue, lightness (also “brightness” or “value”), and saturation (also “chroma” or “intensity”) (Figure 5.2.1). Some people regard these “alternative terms” as completely synonymous with each other, while others argue that they each refer to something specific. For now, just know that the synonymous terms refer to roughly the same properties.
Color is produced when light is either reflected off of (e.g., a car; a printed map) or emitted by (e.g., a computer screen) an object. Hue refers to the portion of the electromagnetic spectrum where human vision is sensitive. We can discuss color falling along that spectrum in terms ofits wavelength of light, from longest (oranges and reds), to shortest (blues and violets). Figure 5.2.2 shows nine swatches of color with different hues, in the order of the rainbow spectrum. It is important to understand that the electromagnetic spectrum offers a vast range of wavelengths, and the human visual system can only perceive a relative tiny portion of that range. For an overview of the electromagnetic spectrum, NASA has a useful website (https://science.nasa.gov/ems/01_intro/(link is external)).
In mapping contexts, hue is typically used to differentiate between features. In general purpose maps, for example, the use of different hues creates different categories, and helps the reader identify different features as belonging to a particular group. In Figure 5.2.3, for example, the color choices are visually distinguishable, and improves the legibility and aesthetics of the map. Though multiple types of roads are shown, all roads are shown in red. Similarly, all hydrologic features and labels are shown in blue - a familiar color easily recognizable by map readers as associated with water. Furthermore, features and their labels that are shown in green, map readers conceptually associate with vegetation.
Lightness is another dimension of color; it describes how perceptually close a color appears to a pure white object. Lightness is also commonly called value, though cartographers sometimes avoid that term, as value is also used to describe data values—using the same word for both items can cause confusion. Another alternative word, brightness, might sound like you’re referring to the brightness of a screen on which a map is being displayed, so use of that word is not recommended either. Lightness works well for visually encoding the order and/or magnitude of thematic data values—typically, lighter colors signify lower data values (i.e., less implies less), and darker, more visually-prominent features implies higher data values.
The third dimension of color is saturation. Saturation is also sometimes called chroma or intensity. Highly saturated colors are particularly useful for calling attention to small but important map elements that would otherwise be lost (Figure 5.2.4). Caution should be used when using saturation in this way, however—the use of too many highly saturated colors, particularly over large areas, may be distracting or accidentally overemphasize unintended features. An effective alternative approach is to desaturate your basemap/background so that your most important features can remain at a reasonable saturation level, but still stand out. If you look at maps in popular media outlets, such as the New York Times or National Geographic, you’ll notice that this approach is extremely common.
The three color dimensions (hue; lightness; saturation) were originally identified by Dr. Albert H. Munsell in the early 20th century. Munsell’s first color model, a color sphere, was an attempt to fit these three dimensions of color into a regular shape. Though this model was still a breakthrough, Munsell realized that it was quite insufficient, as human color perception is not linear and cannot be accurately modeled by a regular shape. The final shape he landed on looks more like a lopsided ellipsoid. The Podcast 99% Invisible has written an excellent short piece on the origins and specifics of the Munsell's color system, with helpful explanatory graphics. Read it here: The Color Sphere: A Professor's Pivotal "Color Space" Numbering System.
Figure 5.2.5 below takes a top-down approach to visualizing this color space: each of the four graphics demonstrates what is, in essence, a slice of the Munsell model, with increasing lightness from left to right. As shown, the colors that the human eye can perceive do not change linearly through color space—note that there is a greater range of red hues than blue hues. This non-linearity makes color specification and design a challenging task.
Student Reflection
Imagine you want to create a categorical map with a large variety of colors. What does Munsell’s model suggest about the kind of colors that would be best used for this purpose?
Though Munsell’s model is helpful for understanding color perception, and perhaps for sharing color specifications with others, a working knowledge of other models is required for building color schemes in GIS and graphic design software. When specifying colors, it is important to consider the display medium that you are using to create them. When mixing paint, cyan, magenta, yellow, and black are used (CMYK [“K” stands for black because it used to refer to the “key plate” in printing and that mixing CMY does not produce a true black, which had the most detail and was usually black]). As mixing paint (or laser printing toner) results in less light being reflected from the color surface, this is called subtractive mixing. The opposite occurs on digital display screens, which create colors by mixing red, blue, and green (RGB) light. Mixing these primaries is called additive mixing.
ArcGIS offers a wide selection of color model choices for specifying colors, including RGB, HSV, and CMYK. RGB and CMYK color models refer to the aforementioned models for mixing additive and subtractive primaries, respectively. RGB is useful for digital media, and CMYK is the color language typically used by graphic artists, largely for print media. Another popular model is hue, saturation, and value (HSV). HSV is reminiscent of the Munsell model (see Figure 5.2.8), but with much greater symmetry—recall the oddly-shaped structure of Munsell’s model.
The symmetry of HSV makes it fit much better into the language of computers, but as human color perception is not linear (recall Figure 5.2.5), using HSV can cause problems unless you remain cognizant of this shortcoming.
Additional color models, including hue, saturation, and lightness (HSL) and Commission internationale de l'éclairage that expresses color as three values: L* (perceptual lightness) and a* and b* (red, green, blue and yellow) (CIEL*a*b* or CIELAB), offer other ways of specifying colors. We will not go further into the details of color specification here, but you are encouraged to explore the recommended readings for more information.
Recommended Reading
Chapter 7: Color Basics. Brewer, Cynthia A. 2015. Designing Better Maps: A Guide for GIS Users. Second. Redlands: Esri Press.