Dot Density
From Wiki.GIS.com
Thematic dot density maps use dots or points to show a comparative density of features over a map based on values stored in polygon layer attribute fields. Attribute values determine the number of dots displayed in the polygon feature. For example, if a polygon feature has a value of 4,000 people and one dot represents 500 people, the map would draw 8 dots, randomly displayed in the polygon.
Attempting to further clarify dot density maps, each dot represents an aggregate of information. For example, a map of a state with dots representing locations of fast food restaurants would not be considered a dot density map. Dots in dot density maps do not represent the locations of things, they represent a summary of data for a given area. A correct application of dot density could be: 50 randomly placed dots on a map of Arkansas might represent 500 rodent roadkill incidents in a year.
Dot density is an effective method to visualize concentrations of quantitative data. In a dot density map, the dots are all the same size and do not represent actual point locations of data. Due to the random placement of the dots within each area represented on the map, it is important to use the smallest unit area possible to display the data. This allows the placement of the dots to be closer to the actual locations of the features being mapped, portraying a more accurate distribution within each area. For example, if the number of farms in each state of the United States was being represented on a dot density map, a state with few farms, such as Arizona, would have dots spread far apart within its boundaries. If a smaller unit area, such as counties, were used to organize the data, the dots would be located closer to their real-world position. [1]
There are four main design principles that should be considered when creating a dot density map:
- The units that are aggregated
- The size of the dot
- The value assigned to the dot
- The location of the dot on the map
Each of these should be carefully considered in designing a dot density map. Changing any one of these can change the overall appearance of the map.
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[edit] Effects of design principles
The dot size used in a dot density map can have a large effect on the patterns seen by the viewer of the map. If the dots are too small, sparse dot patterns will be created on the map. This also can raise doubts in the accuracy of the data on the map. If the dots are too large, the opposite problems arise. The dot patterns become very dense and this creates accuracy problems as well. It is best to use an intermediate dot size to represent the data on the map. When considering dot size it is important to use the dot value in coordination with dot size in determining both of these attributes. They work hand in hand in conveying the right message to the viewer. It is important to use simple rounded numbers for the dot value. This helps communicate the purpose of the map.[2]
[edit] Random Dot Placement
Pseudo-random dot placement with a maximum overlap constraint for dot pairs appears to better mimic how cartographers have traditionally placed dots. Pseudo-random dot placement can be thought of as similar to rigid random placement of circles in a square with maximum circle overlap limits from 0% (mutually exclusive dots) to 100% (totally random dots). Thinking of dot placement in this manner allowed a general equation for aggregate dot area to be devised as a linear combination of the mutually exclusive and totally random dot endpoint equations. Aggregate areas predicted by this general equation were found to closely match actual assemblages of pseudo-random dots with differing maximum dot pair overlaps.
[edit] Sources
- ESRI Web Help - Using Dot density layers
- http://www.geovista.psu.edu/publications/2010/Roth_2009_EG.pdf
- http://downloads2.esri.com/MappingCenter2007/resources/presentations/Kimerling_2008_UR_Colloquium.pdf
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