This week we explored dot mapping, which uses small dots to indicate occurrences of specific geographic phenomena. Each dot represents a set number of instances of the phenomenon being mapped, and the number of dots in an enumeration unit is proportional to the number of real-world phenomenon in the same area. Dot mapping is a good way of visualizing spatial distribution, as it brings out patterns nicely, especially if care is taken to place dots in areas where the phenomenon in question is most likely to occur, by using other geographic features that affect the phenomenon as a guide to dot placement.
As an example, the lab assignment this week uses dots to represent the population of southern Florida. We used census counts, with counties as the enumeration unit. In my map, below, each dot represents 20,000 people. The map was created in ArcMap with some finishing touches applied in Adobe Illustrator. (And I've realized after the fact that the title should say "population distribution" rather than "population density"--oops!)
Without additional input from the mapmaker, ArcMap places dots randomly throughout enumeration units. So, we used an additional layer (not shown in the final map) extracted from a landcover type dataset to have ArcMap place dots only within urban land areas--in other words, developed areas where we know people actually live. This gives us a more realistic and accurate distribution map that allows us to see where the human population is concentrated (with the highest density occurring along the southeastern coast around Miami) and where it is more dispersed (such as much of the interior of this part of the state).
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