6.3: Map Types

Maps are the product, the output, of the cartographic communication process. There are several types of maps, usually divided into two categories: general purpose and thematic. General-purpose maps show the location of roads, rivers, institutions, and land covers. Thematic maps depict particular economic, social, demographic, political, or environmental themes like population density, age distribution, political party preference, income, or malaria. The discussion below describes some of the most frequently used thematic maps and includes some conditions for each of their use. It might be helpful to review the portion of Chapter 2 on data types (including levels of measurement) before reading this section.

Dot Density Map

Thematic dot maps use dots or points to show a comparative density of features over a base map (see Figure 6.3). The dots are all the same size. Most dot maps are vector based and usually do not originate from point layers. They derive their dots from values stored in polygon layer attribute fields. Each polygon’s attribute value dictates the number of dots displayed across the polygon feature. For instance, if one of your polygon features had a value of 2,223 cattle and you decided to represent 500 cattle with one dot, the map would have four dots randomly draped over the polygon.

Data type: Interval
Feature type: Polygon (sometimes point)

Figure 6.3: Dot density map.

Isoline (Isarithmic) Map

Isoline maps use continuous lines (sometimes called isolines or contours) to reference differences across a continuous surface. Lines connect places that have the same value. They require at least ordinal data, but generally use interval or ratio data.

Two types of isoline maps exist: Isometric maps contain absolute data, which is based on scanning the entire surface. Remote sensing imagery is a good example. Isometric maps are largely raster-based due to the continuous nature of the layer. Isopleth maps, the second type, create continuous data from discrete data. In other words, it derives a continuous surface from multiple known locations where measurements were taken (locations in a point layer) (See Figure 6.4). Temperature and rainfall maps are good examples. These maps are both raster and vector based.

Data type: Interval or Ratio (sometimes ordinal)
Feature type: Raster or point

Figure 6.4: Isoline map.

Graduated Symbol Map

Graduated symbol maps use symbols that occur at points across a map, but unlike dot maps, the symbol size varies based on quantity or magnitude (see Figure 6.5). Usually one graduated symbol is generated from within each polygon feature, and its symbol size is determined by the polygon’s attribute value. Higher values get larger symbols. Graduated symbol maps depict ordinal or interval data. The symbols can be circles, squares, or just about any form. Point feature layers can also be used to create graduated symbol maps.

There are two kinds of graduated symbol maps (both are vector based): Proportional symbol maps have symbols that are equivalent to the quantity represented. Range graded symbol maps use a user-defined number of classes each with a different-sized graduated symbol to represent its magnitude. Each symbol represents a range of values, not a single value.

Data type: Ordinal and Interval
Feature type: Polygon and point

Figure 6.5: Graduated symbol map.

Choropleth Map

Choropleth maps are the most common and easily recognized of the thematic maps (see Figure 6.6). They show ratios, proportions, and percentages that are aggregated within polygon features. They use grays and colors to depict each polygon’s (or each pixel’s) attribute value. An election map, depicting shaded states of blue or red—based on the percentage of votes cast for a politician or a party—is an example. Like graduated symbol maps, choropleth maps have proportional and range graded variations, but true choropeths only use ratio data. Simpler “shade” or “color” maps use nominal or ordinal data.

Data type: Rate, proportion, or percentage
Feature type: Raster or Polygon

Figure 6.6: Choropleth map.

Cartogram

Cartograms distort polygon shape to depict the magnitude of attribute data (see Figure 6.7). A high value within a normally small geographic unit (polygon) creates a large geographic unit on the map because the size of the polygon is based on the feature’s attribute value. There are different types of cartograms; they vary on the degree to which the geography is preserved. Broadly, there are two types of cartograms: Non-continuous is the simplest and easiest to construct. The polygons do not need to touch each other. They grow and shrink, but they maintain their shape. Contiguous cartograms maintain their connections with each other, but to do this, they distort the shape of their polygons. Cartograms are vector-based, but most commercial software packages do not have a routine to create cartograms.

Data type: Interval and Ratio
Feature type: Polygon

Figure 6.7: Cartogram.

Flow Map

Flow maps show the movement of goods, people, and ideas between places (see Figure 6.8). Usually they depict interval data by differentiating the width of the lines connecting places. Simpler types of flow maps could depict nominal and ordinal data. Flow maps are vector-based, but most commercial software packages do not have sophisticated flow-mapping routines.

Data type: Interval
Feature type: Line

Figure 6.8: Flow map.

Density Map

Density maps depict the concentration of points (and less often lines) across a continuous surface (see Figure 6.9). Conceptually, each point in the feature layer spreads out its presence beyond its immediate location to include adjacent areas. Then, each cell in the raster output image makes a circular search around itself to determine how many points (or lines) fall within the circular radius. These maps most often depict feature counts, but density can also be derived from one of the point layer’s attribute fields.

Data type: Interval
Feature type: Point

Figure 6.9: Density map.