isoline A map containing continuous lines joining all points of identical value. A map made up of lines that join points of equal value (An example is a contour map which has lines of equal elevation)
A choropleth map is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita income. It provides an easy way to visualize how a measurement varies across a geographic area. Choropleth is often misspelled as chloropleth - with an extra "L" - because it is mistakenly assumed that the name of the map refers to its use of colour.
Map forms
Choropleth maps
These maps, where each spatial unit is filled with a uniform color or pattern, are appropriate for data that have been scaled or normalized in some way. For example, density information, expressed as "per unit area," is appropriately represented using a choropleth map. Tax rates, expressed as "per cent," are also a form of ratio data, which is most easily and correctly visualized using choropleth maps. Choropleth maps are also appropriate for indicating differences in kind of an area data, like ownership or use of land or type of forest cover.
The purple fills of the Czech voting results map represent percent of eligible voters who voted. This representation is (correctly) a choropleth map.
Isopleth maps
Isopleth maps differ from choropleth maps in that the data is not aggregated to a pre-defined unit like a political area or watershed basin. These maps can take two forms:
Lines of equal attribute value are drawn such that all values on one side are higher than the "isoline" value and all values on the other side are lower, or Ranges of similar attribute value are filled with similar colors or patterns. This type of map is used to represent continuous area data that varies smoothly over space. Temperature, for example, is a phenomenon that should be mapped using isoplething, since temperature exists at every point (is continuous), yet does not change abruptly at any point (like tax rates do as you cross into another political zone). Elevation maps should always be in isopleth form for this reason.
Proportional symbol maps
As the name implies, these maps scale icons (most often circles) according to the data they represent. Proportional symbol maps are not dependent on the size of the spatial unit associated with its attribute. In other words, on a proportional symbol map of Europe, tiny Liechtenstein would have the same visual importance as Spain if their respective attribute values were the same. This would not be the case with a choropleth map.
Scaling proportional symbols. Much research has gone into the optimal scaling for proportional symbols. As a general rule, make sure that the area, rather than linear proportions like radius or length of a side, is the scaled parameter. For example, if there are four times as many cars in Los Angeles County than in Orange County, the area of the symbol should be four times greater for Los Angeles County. If the symbol choice is a circle, the radius of the Los Angeles symbol should thus be only twice as great (since area scales with the square of the radius).
The total number of voters in each Czech district is represented with proportional symbols on the Czech voting results map.
Dot maps
Used to represent themes that vary smoothly over space but are discrete, dot maps create a visual impression of density by placing a dot or some other symbol in the approximate location of one or more instances of the variable being mapped. Dot maps should be used only for raw data, not for data normalized or expressed as a ratio. Appropriate themes for dot maps include livestock farms, utility poles, and population distribution in a region.
Dot map parameters. When constructing a dot map, two parameters must be considered: the graphical size of each dot and the value associated with each dot. For example, you might stipulate that each dot be 2 pixels in diameter, and each represent 100 persons. In general, many small dots, each representing relatively few instances of the attribute, is more effective than a few large dots, but is more tedious to construct.
Warning: Dot map generation in present GIS is, from a cartographic standpoint, fatally flawed in that dots are arranged within each spatial unit in a random fashion. For example, a dot map of alligator population aggregated to the entire U.S. would be rendered with just as many dots in Iowa as in Florida. To create a dot map that does not mislead, the map must be saved as a vector image and brought into a drawing package like FreeHand or Illustrator, where each dot is physically moved to a more logical location. Unless you wish to go to this trouble, dot maps should be used only for very detailed spatial information (for example, county- or township-level data of alligator population for the entire U.S.) or with a great deal of caution and awareness.
Many reference maps could be considered dot maps, the location of each dot representing the location of a point of interest, a building, or some other discrete point information.
