6/19/2011 Maps for the 2010 Census, Part 2

It has been a great experience watching the emergence of GIS and Thematic Cartography over the past 10 years. The ubiquity of Google Maps and in-vehicle navigation systems has made everyone more "Geo-aware". Working off this greater geo-awareness, the private-sector media has expanded its presentations of Thematic Maps. I especially like those in USA Today:


Here is the link to the "Unmarried couples" map/article:Unmarried couples map/article


Here is the link to the "Fewer kids" map/article:Fewer kids map/article

3 reasons why I like these maps:
- the # of ranges is manageableFor a single-color ramp (the blues in the Unmarried map), 5 ranges from white-to-dark-blue is easily comprehended, and clustering (or lack thereof) is readily apparent. The "Fewer kids" map is actually easier: 2 color ramps of only 3 colors each (3 above-and-below the U.S. average), with the colors going from light-to-dark according to intensity.
- the borders do not get in the way of the maps Although the data is presented at the county-level, the county boundaries are very subtle in both cases (light blue or light gray). This allows both the colors to stand-on-their-own, and the states themselves can be identified by their own unique black borders.
- the use of color ramps In the Unmarried map, I intuitively understand that dark-blue is "more" than light-blue/white. Knowing this allows me to concentrate on the map, and not have to keep referring back to the legend (is blue higher than yellow? is green more than red?). Although the "Fewer kids" map has two sets of color-ramps, once I know the reds are more/gain and the blues are less/loss, I can just focus my attention on the map.

Another area of mapping at USA Today is their Census 2010 data page:
Here is the link to the USA Today Census 2010 data website:Census 2010 link

This website is interactive - click on a state, and the bar-graph statistics change appropriately while the new county-level map is drawn. It is very smooth and looks good. Needless to say, these visualizations are inspirational - I want to learn how to do this with my data!