Now that we know what maps are for, we can discuss which types are best for what purpose. There is no fixed classification of map types in the literature, but there are some well-known types of maps that can be distinguished:
- Choropleth maps
- Proportional symbol maps
- Isopleth maps
- Dot maps
This classification is incomplete and open-ended!
1 Chloropleth maps
Before going further, read: Slocum et al. (2004). Thematic Cartography and Geographic Visualization. 2nd ed. Prentice Hall. – Section 4.4.1 (pp. 64-66) and Section 13.1 (pp. 250-252).
Choropleth maps are the prototypical thematic maps. The name is composed of the Greek words plethus meaning quantity and choros meaning space. Choropleth maps depict attributes related to regions. They show the values of these attributes, i.e. the qu antities, by areal symbols. These are shadings, colors, or patterns. Here is an example of a choropleth map.
A problem is that some count values depend on region size. If the size of enumeration units is not as homogeneous as the size of counties in the map of Georgia, comparisons become difficult or uninteresting. You would probably not be surprised to hear that the population in the USA is bigger than in Monaco, because Monaco is much smaller than the USA.
A more interesting comparison between the two countries is one that eliminates the effect of different region size, as is done with population density. Density figures report the population referring to an area of equal size, say one square kilometer. You divide the population figure of each region by the size of that region, resulting, for example, in population per square kilometer. The principle of adjusting raw totals for differing sizes of enumeration units is called standardization.
It applies to all four map types. But pay attention only to use standardization when the count value actually depends on the region size. This is, for example, not true for the number of days with sunshine: a bigger country would not have more days with sunshine than a smaller one due to the difference in size.
The following two maps show the effect of standardization. In the left map, total numbers are depicted without standardization. The big dark colored district in the southeast has a high value; it belongs to the highest class. In the right map, where the population figures have been standardized by the area this district appears in the light color of the lowest class. This reveals that the large number of inhabitants was caused by the size of the region. Such drastic changes are less likely for smaller regions: compare the two maps.
There are different standardization approaches. The numerator and denominator may be areas or not, yielding four possible combinations. Examples are:
- inhabited area (area) / area of enumeration unit (area)
- inhabitants (no area) / area of enumeration unit (area)
- inhabited area (area) / number of residential zones (no area)
- number of apartment houses (no area) / number of houses (no area)
Pros and cons of choropleth maps:
- + easy to produce and read
- + distribution patterns are easy to recognize
- – badly misleading if inappropriately standardized
- – cannot show variability within regions
- – regions are often not appropriate for a theme
- – most common pitfall: colors for quantities
2 Proportional symbol maps
Before going further, read: Slocum et al. (2004). Thematic Cartography and Geographic Visualization. 2nd ed. Prentice Hall. – Section 4.4.2 (pp. 66-69) and Section 13.1 (pp. 310-321).
Proportional symbol maps present data by symbols or diagrams located at points. The size of the symbol reflects the amount of the phenomenon. Here is an example of a proportional symbol map, using the most popular symbol, the circle. It shows the same information as the choropleth map of Georgia’s total population in the previous section.
The data are not standardized. This could be done, for example, by dividing them by the area. In this example, the point data are conceptual, because they do not refer to a point, but describe an areal phenomenon. The symbols are geometric. The scaling is mathematical and thus does not account for the psychological effect of underestimating large symbols. But perceptual scaling would have enlarged the already large circles in the northern area, where cluttering occurs. In other parts of the map, the circles are nearly invisible – a problem of the wide range covered by the raw data. In order to avoid this effect, the data could be classed so that a fixed number of symbols results, which can be drawn in reasonable sizes.
Pros and cons of proportional symbol maps:
- + large, open-ended choice of possible symbols from circles through bars to Chernoff faces etc.
- + no need to aggregate data to fixed regional units
- – distribution patterns can be difficult to recognize
- – danger of visual clutter
3 Isopleth Maps
Before going further, read: Slocum et al. (2004). Thematic Cartography and Geographic Visualization. 2nd ed. Prentice Hall. – Overview of chapter 14 (pp. 271-272), Section 14.1 (p. 272) and Section 14.7 (p. 275), Summary of chapter 14 (pp. 289-290).
Isopleth maps are used to depict smooth continuous phenomena. These phenomena are represented by interpolating lines of equal values (isolines). The name “isopleth” is specifically used when conceptual point data are represented, i.e. values are not measured at point locations, but collected over areas. Otherwise, the term “isometric” is used. Smooth continuous phenomena are, for example, height and temperature. They are measured at point locations, i.e. they are true point data. The interpolation leads to lines of equal height (contour lines) or lines of equal temperature (isothermes). Probably you have already seen such isolines on topographic maps and weather maps. If conceptual point data shall be interpolated, they must be standardized in order to account for the area over which they have been collected. Isopleth maps can be misused when applied to non-continuous phenomena. Consider population data that are collected on basis of enumeration units, for example in the area of São Paulo. For each unit a figure representing the population density in this unit is available.
The next graphic shows an isopleth map. A centroid has been placed in each unit and the population density figure has been attached to it. Then isopleths have been interpolated between the centroids. This gives the impression that, for example, in the city of São Paulo population density gradually changes northwards and southwards.
But this differentiation within the enumeration units is not contained in the data; it is only an artefact. A choropleth map is an appropriate depiction of the data, because the data only provides one value for each unit.
There are various methods of interpolation:
- inverse-distance weighting
- kriging (optimal interpolation)
And there are different ways to symbolize the interpolated data.
- contour lines
- hypsometric tint
- continuous-tone map
Pros and cons of the interpolation method
- + familiar from topographic maps (terrain representation)
- + one type of map for continuous phenomena
- – often misused
- – suggesting detail that is not there
4 Dot Maps
Before going further, read: Slocum et al. (2004). Thematic Cartography and Geographic Visualization. 2nd ed. Prentice Hall. – Section 17.1-3 (pp. 329-335).
Dot maps have become increasingly popular. They are a good alternative for choropleth maps. Each dot in a dot map represents a fixed value. For population data, for example, this can be one inhabitant or any other amount. If additional information on location is available, it can be used for positioning the dots. Thus it can, for example, be avoided to place inhabitants in lakes. For the following example no additional information was available.
Pros and cons of dot maps:
- + show finer detail, actual distribution patterns
- + production made easier through GIS
- – information needs
- – unfamiliar
5 Overview of Map Type Classification
The four map types presented here can be distinguished according to three criteria:
- What kinds of symbols are used…
- point (i.e., a symbol located at a point)
- linear (isolines)
- areal (shaded, colored)
- …to represent what phenomena
- quantities and locations
- …to answer what questions?
- distribution patterns
- individual values
The following table shows how the map types fit in a matrix of the first two criteria.
|Symbol / represents||point||linear||areal|
|quantity||Proportional symbol maps|
|location||(place maps)||(road maps)||(political maps)|
|quantity and location||dot maps||isopleth maps||choropleth maps|
You have seen that each type has its pros and cons. Often multiple views are useful to shed light on something from the different perspectives. Also, map types can be combined in one map. Think, for example, of a choropleth map with proportional symbols.
Finally, it shall be stressed again that there are more types than appear in this classification. The next map, a cartogram, gives an example. In cartograms, the area of the enumeration units is sized according to the value depicted. Units with high values extend, units with low values contract.
“The two-variable contiguous area cartogram … depicts enumeration units proportionally scaled to the data that they represent. In addition, traditional choropleth shading is applied, showing the States won by each candidate. The size of each state is transformed based on the magnitude of electoral votes, emphasizing the variable that carries the crucial election information. The size of the red areas has decreased dramatically. The length of the bars in the legend refers to the amount of observations falling in each category (# of won states per candidate).” (Fabrikant, 2000)