3.1 Color

Although a high-quality map is composed of many different elements, color is one of the first components noticed by end-users. This is because we each have an intuitive understanding of how colors are, and should be, used to create a compelling and pleasing visual experience. Nevertheless, it is not always clear to the mapmaker which colors should be used to convey the purpose of the product best. This intuition is much like listening to our favorite music. We know when a note is in tune or out of tune, but we would not necessarily have any idea of how to fix a bad note. Color is indeed a tricky piece of the cartographic puzzle and is not surprisingly the most frequently criticized variable on computer-generated maps. This section attempts to outline the essential components of color and the guidelines to most effectively employ this vital map attribute.

Color Basics

As electromagnetic radiation (ER) travels via waves from the sun (or a lightbulb) to objects on the earth, portions of the ER spectrum are absorbed, scattered, or reflected by various objects. The resulting property of the absorbed, scattered, and reflected ER is termed “color.” White is the color resulting from the full range of the visual spectrum and is therefore considered the benchmark color by which all others are measured. Black is the absence of ER. All other colors result from a partial interaction with the ER spectrum.

The three primary aspects of color that must be addressed in map making are hue, value, and saturation. Hue is the dominant wavelength or color associated with a reflecting object. Hue is the most fundamental component of color and includes red, blue, yellow, purple, and so forth. Value is the amount of white or black and is often synonymous with contrast. Variations in the amount of value for a given hue result in varying degrees of lightness or darkness for that color. Lighter colors are said to possess high value, while dark colors possess low value. Monochrome colors are groups of colors with the same hue but with incremental variations in value. Variations in value will typically lead the viewer’s eye from dark areas to light areas.


Saturation describes the intensity of color. Full saturation results in pure colors, while low saturation colors approach gray — variations in saturation yield different shades and tints. Shades are produced by blocking light, such as by an umbrella, tree, curtain, and so forth. Increasing the amount of shading results in grays and blacks. A tint is the opposite of shade and is produced by adding white to a color. Tints and shades are particularly germane when using additive color models. To maximize the interpretability of a map, use saturated colors to represent hierarchically prominent features and washed-out colors to represent background features.

If used properly, color can greatly enhance and support map design. Likewise, color can detract from a mapping product if abused. To use color properly, one must first consider the purpose of the map. In some cases, the use of color is not warranted. Grayscale maps can be just as effective as color maps if the subject matter merits it. Regardless, there are many reasons to use color. The five primary reasons are outlined here.

Color is particularly suited to convey meaning. For example, red is an intense color that evokes a passionate response in humans. Red has been shown to evoke physiological responses such as increasing the rate of respiration and raising blood pressure. Red is frequently associated with blood, war, violence, even love. On the other hand, blue is a color associated with calming effects. Associated with the sky or ocean, blue colors can assist in sleep and is, therefore, a recommended color for bedrooms. Too much blue, however, can result in a lapse from calming effects into feelings of depression (i.e., having the “blues”). Green is most commonly associated with life or nature (plants). The color green is undoubtedly one of the most topical colors in today’s society with commonplace references to green construction, the Green party, going green, and so forth.

Green, however, can also represent envy and inexperience (e.g., the green-eyed monster, greenhorn). Brown is a natural color that can represent earth tones, but can also imply dullness. Yellow is most commonly associated with sunshine and warmth. Yellow can also represent cowardice (e.g., yellow-bellied). Black, the absence of color, is possibly the most meaning-laden color in modern parlance. Even more than the others, the color black purports surprisingly strong positive and negative connotations. Black conveys mystery, elegance, and sophistication (e.g., a black-tie affair, in the black), while also conveying loss, evil, and negativity (e.g., blackout, black-hearted, black cloud, blacklist).


The second reason to use color is for clarification and emphasis. Warm colors, such as reds and yellows, are notable for emphasizing spatial features. These colors will often jump off the page and are usually the first to attract the reader’s eye, particularly if they are counterbalanced with cool colors, such as blues and greens. Also, the use of a hue with high saturation will stand out starkly against similar hues of low saturation.

Color use is also vital for creating a map with pleasing aesthetics. One of the most challenging aspects of map creation is developing a useful color palette. When looking at maps through an aesthetic lens, we are truly starting to think of our creations as artwork. Although somewhat particular to individual viewers, we all have an innate understanding of when colors in a graphic/art are aesthetically pleasing and when they are not. For example, color use is considered harmonious when colors from opposite sides of the color wheel are used, whereas equitable use of several significant hues can create an unbalanced image.

The fourth use of color is abstraction. Color abstraction is an effective way to illustrate quantitative and qualitative data, particularly for thematic products such as choropleth maps. Here, colors are used solely to denote different values for a variable and may not have any particular rhyme or reason.


Opposite of abstraction, color can also be used to represent reality. Maps showing elevation (e.g., digital elevation models or DEMs) are often given false colors that approximate reality. Low areas are colored in variations of green to show areas of lush vegetation growth. Mid-elevations (or low-lying desert areas) are colored brown to show sparse vegetation growth. Mountain ridges and peaks are colored white to show accumulated snowfall. Watercourses and water bodies are colored blue. Unless there is a specific reason not to, natural phenomena represented on maps should always be colored to approximate their actual color to increase interpretability and to decrease confusion.

Greens, blues, and browns are used to imitate real-world phenomena.

Color Models

Color models are systems that allow for the creation of a range of colors from a shortlist of primary colors. Color models can be additive or subtractive. Additive color models combine emitted light to display color variations and are commonly used with computer monitors, televisions, scanners, digital cameras, and video projectors. The RGB (red-green-blue) color model is the most common additive model. The RGB model combines light beams of the primary hues of red, green, and blue to yield additive secondary hues of magenta, cyan, and yellow. Although there is a substantive difference between pure yellow light (~580 nm) and a mixture of green and red light, the human eye perceives these signals as the same. The RGB model typically employs three 8-bit numeric values (called an RGB triplet) ranging from 0 to 255 to model colors. For instance, the RGB triplets for the pure primary and secondary colors are as follows:

  • Red = (255, 0, 0)
  • Green = (0, 255, 0)
  • Blue = (0, 0, 255)
  • Magenta = (255, 0, 255)
  • Cyan = (0, 255, 255)
  • Yellow = (255, 255, 0)
  • Black, the absence of additive color = (0, 0, 0)
  • White, the sum of all additive color = (255, 255, 255)

Two other common additive color models, based on the RGB model, are the HSL (hue, saturation, lightness) and HSV (hue, saturation, value) models. These models are based on cylindrical coordinate systems whereby the angle around the central vertical axis corresponds to the hue; the distance from the central axis corresponds to saturation, and the distance along the central axis corresponds to either saturation or lightness. Because of their basis in the RGB model, both the HSL and HSV color models can be directly transformed between the three additive models. While these relatively simple additive models provide minimal computer-processing time, they do possess the disadvantage of glossing over some of the complexities of color. For example, the RGB color model does not define “absolute” color spaces, which connotes that these hues may look differently when viewed on different displays. Also, the RGB hues are not evenly spaced along the color spectrum, meaning combinations of the hues is less than exact.

Additive Color Model

In contrast to an additive model, subtractive color models involve the mixing of paints, dyes, or inks to create full-color ranges. These subtractive models display color on the assumption that white, ambient light is being scattered, absorbed, and reflected from the page by the printing inks. Subtractive models, therefore, create white by restricting ink from the print surface. As such, these models assume the use of white paper as other paper colors will result in skewed hues. CMYK (cyan, magenta, yellow, black) is the most common subtractive color model and is occasionally referred to as a “four-color process.” Although the CMY inks are sufficient to create all of the colors of the subtractive rainbow, a black ink is included in this model as it is much cheaper than using a CMY mix for all blacks (black being the most commonly printed color) and because combining CMY often results in more of a dark brown hue. The CMYK model creates color values by entering percentages for each of the four colors ranging from 0 percent to 100 percent. For example, pure red is composed of 14 percent cyan, 100 percent magenta, 99 percent yellow, and 3 percent black.

As you may guess, additive models are the preferred choice when maps are to be displayed on a computer monitor, while subtractive models are preferred when printing. If in doubt, it is usually best to use the RGB model as this supports a more significant percentage of the visible spectrum in comparison with the CMYK model. Once an image is converted from RGB to CMYK, the additional RGB information is irretrievably lost. If possible, collecting both RGB and CMYK versions of an image is ideal, mainly if your graphic is to be both printed and placed online. One last note, be selective in the use of file formats for these color models. The JPEG and GIF graphic file formats are the best choices for RGB images, while the EPS and TIFF graphic file formats are preferred with printed CMYK images.

Subtractive Color Model

Color Choices

Effective color usage requires an understanding of the color wheel. Invented by Sir Isaac Newton in 1706, the color wheel is a visual representation of colors arranged according to their chromatic relationships. Primary hues are equidistant from each other with secondary and tertiary colors intervening. The red-yellow-blue color wheel is the most frequently used; however, the magenta-yellow-cyan wheel is the preferred choice of printmakers (for reasons described in the previous section). Primary colors are those that cannot be created by mixing other colors; secondary colors are defined as those colors created by mixing two primary hues; tertiary colors are those created by mixing primary and secondary hues. Furthermore, complementary colors are placed opposite each on the wheel, while analogous colors are located proximal to each other. Complementary colors emphasize differences. Analogs suggest harmony.

Color Wheel

Colors can be further referred to as warm or cool. Warm colors are those that might be seen during a bright, sunny day. Cool colors are those associated with overcast days. Warm colors are typified by hues ranging from red to yellow, including browns and tans. Cool color hues range from blue-green through blue-violet and include the majority of gray variants. When used in mapping, it is wise to use warm and cool colors with care. Indeed, warm colors stand out, appear active, and stimulate the viewer. Cool colors appear small, recede, and calm the viewer. Apply warm colors to the map features of primary interest, while using cool colors on the secondary, background, and contextual features.

Warm (Orange) and Cool (Blue) Colors

In light of the plethora of color schemes and options available, it is wise to follow some basic color usage guidelines. For example, changes in hue are best suited to visualizing qualitative data, while changes in value and saturation are effective at visualizing quantitative data. Likewise, variations in lightness and saturation are best suited to representing ordered data since these establish a hierarchy among features. In particular, a monochromatic color scale is an effective way to represent the order of data whereby light colors represent smaller data values, and dark colors represent larger values. Keep in mind that it is best to use more light shades than dark ones as the human eye can better discern lighter shades. Also, the number of coincident colors that can be distinguished by humans is around seven, so be careful not to abuse the color palette in your maps. If the data being mapped has a zero point, a dichromatic scale provides a natural breaking point with increasing color values on each end of the scale representing increasing data values.

Also, darker colors result in more important or pronounced graphic features (assuming the background is not overly dark). Use dark colors on features whose visual impact you wish to magnify. Finally, do not use all the colors of the spectrum in a single map. It is best to leave such messy, rainbow-spectacular effects to the late Jackson Pollock and his abstract expressionist ilk.


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Introduction to Geographic Information Systems by R. Adam Dastrup, MA, GISP is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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