Color Use Guidelines for Mapping and Visualization

Cindy Brewer

 The graphic display of data plays a critical role in visualization and exploratory data analysis. Appropriate use of color for data display allows interrelationships and patterns within data to be easily observed. The careless use of color will obscure these patterns. When color is used `appropriately,' the organization of the perceptual dimensions of color corresponds to the logical ordering in the data. The color scheme typology I present matches a comprehensive listing of the ways in which data are organized with corresponding organizations of hue and lightness.

 The scheme guidelines are limited to the use of color to directly represent data that occur at locations in the graphic where colors occur. The types of thematic maps to which these guidelines apply are choropleth maps (for example, census tracts filled with colors representing the percentage of the population from an ethnic group), filled isoline maps (for example, color bands that mark set ranges of terrain elevation), and qualitative areal-extent maps (for example, different colors for different types of vegetation). My hope is that these guidelines and the associated terminology will also guide the work of people grappling with data visualization challenges in diverse disciplines such as physics, medicine, psychology, and graphic arts.

 A disorderly jumble of colors produces a map that is little more than a spatially arranged look-up table. The goal of this WWW resource is to help you do better than that by using color with skill. This resource provides a generalized set of color schemes and example maps.


Color Scheme Types and Combinations: Overview

Select the color scheme of interest below to see examples of it in use.


Binary Color Schemes

Binary schemes show nominal differences that are divided into only two categories. The primary perceptual difference between the two categories of a binary scheme may be a lightness step, unlike the use of hue for multi-valued qualitative variables. Incorporated versus unincorporated urban areas are well represented by a binary color scheme.

 Binary Color Scheme Example



Diverging Color Schemes

Diverging schemes allow the emphasis of a quantitative data display to be progressions outward from a critical midpoint of the data range. A typical diverging scheme pairs sequential schemes based on two different hues so that they diverge from a shared light color, for the critical midpoint, toward dark colors of different hues at each extreme. Deviations above and below the median death rate from a disease, for example, are well represented by a diverging color scheme.

Diverging Color Examples


Diverging Color Schemes: Munsell Charts



Diverging Binary and Diverging Sequential Color Schemes

Diverging/binary and diverging/sequential schemes have the same perceptual characteristics. The success of the schemes hinge on the large contrast range available in the lightness dimension. Large lightness steps are used for the binary or sequential variable. Smaller lightness steps, that are bolstered by a change in hue, represent the diverging component of the scheme within each large lightness step of the comparison variable. For example, data on cancer rates above and below a mean rate (diverging) and air pollution levels (sequential) are well represented by a diverging/sequential color scheme.

  Diverging Binary Color Example

 Diverging Sequential Color Example



Diverging Diverging Color Schemes

Diverging/diverging schemes are the only two-variable schemes that depart from the idea of a direct overlay of the component one-variable schemes. Place a different moderately-dark hue at each of the four corners of the legend. These four hues represent categories that are extremes for both variables. Place a very light or white color at the center of the legend, creating an appropriately light color for the class that contains the critical value or midpoint of both variables. The remaining colors are lighter than the corners, because they contain the midpoint of one of the two variables, and they are transitional hues that lie between their adjacent hues. The color circle is essentially stretched around the perimeter of the legend and lightness adjusted in response to critical values within the data ranges of both variables. Areas above and below the poverty line in 1960 and 1990, for example, are well represented by a diverging/diverging color scheme.

 Diverging Diverging Color Example



Qualitative Color Schemes

Qualitative schemes use differences in hue to represent nominal differences, or differences in kind. The lightness of the hues used for qualitative categories should be similar but not equal. Assign the lightest, darkest, and most saturated hues in the scheme to categories that warrant emphasis on the map. Data about land use or land cover, for example, are well represented by a qualitative color scheme.

 Qualitative Color Example

 Qualitative Color Schemes: Munsell Charts



Qualitative Binary Color Schemes

In qualitative/binary schemes, light and dark versions of each hue of the qualitative variable correspond to the binary variable categories. Binary/binary schemes are a subset of the qualitative/binary schemes with one binary difference represented by a hue difference and the other by a lightness difference. A multi-hued vegetation map (qualitative) with darker hues for vegetation on public lands and lighter hues for vegetation on private lands (binary) is well suited by a qualitative/binary color scheme.

 Qualitative Binary Color Example



Qualitative Sequential Color Schemes

In qualitative/sequential schemes, the qualitative variable is represented with hues and the quantitative variable is represented with sequences of lightness steps within each hue. Binary/sequential schemes are a subset of qualitative/binary schemes with the binary variable represented by a hue difference and lightness differences reserved for the sequential variable. Population percentages (sequential) of varied dominant ethnic groups or religions (qualitative), for example, are well represented by a qualitative/sequential color scheme.

 Qualitative Sequential Color Example



Sequential Color Schemes

Sequential data classes are logically arranged from high to low, and this stepped sequence of categories should be represented by sequential lightness steps. Low data values are usually represented by light colors and high values represented by dark colors. Transitions between hues may be used in a sequential scheme, but the light-to-dark progression should dominate the scheme. Terrain slope categories or population densities, for example, are well represented by sequental color schemes.

 Sequential Color Example

 Sequential Color Schemes: Munsell Charts



Sequential Sequential Color Schemes

Sequential/sequential schemes are the logical mix of all combinations of the colors in two sequential schemes. Thus, the schemes are based on two hues. The hue mixtures may form a third hue (magenta and cyan sequences produce a variety of transitional purple-blues). If the two hues crossed are approximate complements, their mixtures produce a neutral gray diagonal and desaturated transitional colors. Systematic lightness differences throughout the scheme are important; do not depend on hue to impart the magnitude message. Use hue transitions to designate differences in proportions of the two variables mapped. For example, data on educational attainment crossed with crime rate categories are well represented by a sequential/sequential color scheme.

Sequential Sequential Color Examples



(C) Jakub Langhammer, 26.3.2002