Module 3: Data Classification Lab Assignment

I tried to decide which method of classification best represented the given data by evaluating which of the four methods offered the clearest picture of the data. It was easy for me to rule out the standard deviation classification because this classification would not allow me to use a color ramp similar to the others. Additionally, with only four breaks in the data, I felt that far too many tracts fell within the smallest break. I felt the same way about the equal interval classification.

I decided that the quantile data classification portrayed the best model of the data. On the map below, I made some key changes to a quantile style map to further enhance the portrayal of the data. First, I created eight breaks. One problem with five breaks was the large range of data included in the 5th class. There is still a significant range in my 8th class; however, I believe that this is appropriate as I am placing an obvious emphasis on demographics. After that, I wanted to change to a color ramp that did not directly correlate with racial demographics. Such a color pattern could be interpreted as insensitive and offensive, and I wanted to avoid this. My final product resulted in a map with enough color variance and enough classes to easily interpret the data provided.

MAP CRITIQUE LAB

http://piratemapster.com/maps/free/PM1209001.gif

Above, you will find my example of a bad map. It is safe to assume that this is a treasure map, and we can only hope that the cartographer's intention was to make the treasure hard to find (or to fill a page in a coloring book). The map has a North seeking arrow; however, the only other geographic references are some poorly defined symbols. Presumably, you are approaching the area by sea, so why not land your craft closer to the "destination" to avoid the walk of doom past the giant bear? Is there cliff in the way, or a rocky coastline?

(http://upload.wikimedia.org/wikipedia/commons/7/73/US_presidential_election_2004_results_by_county.jpg)

Above is my example of a good map. This map illustrates the 2008 presidential election results by county. Sen. John McCain received a majority of the votes in the red counties. President Obama received a majority of the votes in the blue counties. This map would be a great foundation for other layers of data such as population density, demographics, and even poverty. The first thing I thought when I saw this map is, "it is really, really red, how did President Obama win?!". A second look at this map confirms that President Obama carried more densely populated areas such as counties in the Northeast, much of the Pacific coast, counties with major cities, and counties where major universities are located. For an example of the significance of demographics, look at how President Obama fared around the US Highway 80 corridor through central Alabama and Georgia. I have titled this area "The Civil Rights Belt". I believe this is a great map because it caused me to think about whole new sets of data, and it inspired more study. My only concern: why is Alaska white?

Off and Running!

We are off and running into a new world of Cartographic Skills!