5. THE DOT DENSITY MAP
A dot density map can also be simply called a dot map. Although any point symbol can be
used, it has become customary to use small dots—thus the name dot density mapping. These are
also quantitative maps; information pertaining to density and distribution is gained by visual
inspection of the spatially arrayed symbols to arrive at relative magnitudes.
In the simplest case, the technique involves the selection of an appropriate point symbol to
represent a quantity of a geographically distributed phenomenon. The symbol form (size, shape,
color, and so on) does not change, but the frequency of dots changes from area to area in
proportion to the number of objects being represented. The technique works best for data that are
tabulated in enumeration areas as totals, and has been used extensively for mapping agricultural
production data and population data; see Figure Dot Density Map below.
Figure Dot Density Map: The elements of the typical dot map include the dots, reference political
boundaries, and a legend that includes dot value and, if possible, representative densities taken from the
map. The reader gets the idea that the amount of the item varies from place to place.
, Advantages and Disadvantages of Dot Density Mapping
The advantages include;
1. The rationale of mapping is easily understood by the map reader.
2. It is an effective way of illustrating variations in spatial density.
3. Original data may be recovered from the map if the map has been designed for that
purpose.
4. More than one data set may be illustrated on the same map. As with any bivariate or
multivariate map, there should be a distributional or functional relationship between the
sets.
5. GIS and mapping software that support this technique allow the cartographer to
quickly view and evaluate many dot value and size combinations with relative ease.
Possible disadvantages of dot mapping would include:
1. Reader perception of dot densities is not linear. A person viewing an area with 10
times the number of actual dots compared with another area will usually not estimate
values in those two areas in the same proportion as depicted by the dots on the map.
2. GIS and mapping software typically randomize dots within enumeration units,
resulting in dots that may not be close to the phenomena they represent.
3. Ancillary data layers or imagery should be used in controlling dot placement, but in
many cases this is not practicable. Possible workarounds are discussed later in the
chapter.
4. Large ranges in data values make it very difficult to select a single dot value that is
visually acceptable across areas of highest and lowest density.
5. When the map has been designed for optimum portrayal of relative spatial density, it is
practically impossible for the reader to recover original data values.
Data Suitability
There are several data considerations that should be made before selecting this method. As with
the choropleth map, this technique is used extensively for data that are tabulated in enumeration
areas. Unlike the choropleth map, where some sort of derived data is generally desirable, totals
or non-derived quantities are used in dot mapping. Common examples include agricultural
production data (such as crops, crop productivity (in bushels or tons), numbers of livestock or
farms), and population totals. In these cases, one dot may represent 500 bushels of harvested
wheat, or 1,000 persons.
Data sets with extremely small or large attribute data ranges are often more difficult to portray
effectively with dot maps than with other thematic map types. Dot maps use a single number to
represent the value of the dot. Data with small attribute ranges will produce a spatial distribution
A dot density map can also be simply called a dot map. Although any point symbol can be
used, it has become customary to use small dots—thus the name dot density mapping. These are
also quantitative maps; information pertaining to density and distribution is gained by visual
inspection of the spatially arrayed symbols to arrive at relative magnitudes.
In the simplest case, the technique involves the selection of an appropriate point symbol to
represent a quantity of a geographically distributed phenomenon. The symbol form (size, shape,
color, and so on) does not change, but the frequency of dots changes from area to area in
proportion to the number of objects being represented. The technique works best for data that are
tabulated in enumeration areas as totals, and has been used extensively for mapping agricultural
production data and population data; see Figure Dot Density Map below.
Figure Dot Density Map: The elements of the typical dot map include the dots, reference political
boundaries, and a legend that includes dot value and, if possible, representative densities taken from the
map. The reader gets the idea that the amount of the item varies from place to place.
, Advantages and Disadvantages of Dot Density Mapping
The advantages include;
1. The rationale of mapping is easily understood by the map reader.
2. It is an effective way of illustrating variations in spatial density.
3. Original data may be recovered from the map if the map has been designed for that
purpose.
4. More than one data set may be illustrated on the same map. As with any bivariate or
multivariate map, there should be a distributional or functional relationship between the
sets.
5. GIS and mapping software that support this technique allow the cartographer to
quickly view and evaluate many dot value and size combinations with relative ease.
Possible disadvantages of dot mapping would include:
1. Reader perception of dot densities is not linear. A person viewing an area with 10
times the number of actual dots compared with another area will usually not estimate
values in those two areas in the same proportion as depicted by the dots on the map.
2. GIS and mapping software typically randomize dots within enumeration units,
resulting in dots that may not be close to the phenomena they represent.
3. Ancillary data layers or imagery should be used in controlling dot placement, but in
many cases this is not practicable. Possible workarounds are discussed later in the
chapter.
4. Large ranges in data values make it very difficult to select a single dot value that is
visually acceptable across areas of highest and lowest density.
5. When the map has been designed for optimum portrayal of relative spatial density, it is
practically impossible for the reader to recover original data values.
Data Suitability
There are several data considerations that should be made before selecting this method. As with
the choropleth map, this technique is used extensively for data that are tabulated in enumeration
areas. Unlike the choropleth map, where some sort of derived data is generally desirable, totals
or non-derived quantities are used in dot mapping. Common examples include agricultural
production data (such as crops, crop productivity (in bushels or tons), numbers of livestock or
farms), and population totals. In these cases, one dot may represent 500 bushels of harvested
wheat, or 1,000 persons.
Data sets with extremely small or large attribute data ranges are often more difficult to portray
effectively with dot maps than with other thematic map types. Dot maps use a single number to
represent the value of the dot. Data with small attribute ranges will produce a spatial distribution
