Isoline Map example

Isolines rock at depicting continuous data. From temperature maps on your local news station, to topographic maps, isolines are your friend in showing continuous data over a spatial plane. The above map forgoes the isoline boundaries, and instead the cartographer made the choice to simply allow the colors to flow from the low values to high values. It is important to note that the above map does not have set intervals for labeling it's isoline values, and since this is a temperature map for non-research purposes this is not terribly surprising -- most temperature maps produced at this scale are labeling temperature at the rough location of major cities (New York City, Washington D.C., Denver, CO, etc).

Bivariate Map example

The above map is an example of a bivariate map, utilizing proportional symbols with a chloropleth underlay. While the data choices are certainly interesting, the map's design deserves some consideration as well. Nicaragua is pushed forward by it's neighboring, grayed out countries, while it itself colorfully standouts with it's yellows, oranges, and blues. Particularly clever of the cartographer is the use of complementary colors (blue and orange) to help both data sets really stand out.

Typhoon Maps

Mapping storm systems is an interesting task that leaves the cartographer with a variety of questions. How much detail does the base map need? How should the storm trajectory be mapped? Should multiple potential storm trajectories be shown, or an extending buffer?

          The reason I chose these two maps in particular is because both find different ways to depict the storm path. The first map simply shows the storm path as a dotted line, with typhoon category bench marks as the storm passes over the Philippines, crosses the South China Sea, makes land fall in Vietnam, and proceeds north the China. On the other hand, the second map chooses to use color and symbol to depict the typhoon's intensity, and the storm trajectory is depicted as an expanding buffer, to underline the reality that the storm could shift course. The second map at depicts estimated times of the typhoon's position, which is also important information  in helping stage potential evacuations that may need to occur for coastal populations.

Bivariate Map

The above map was created using 2010 U.S. Census data, and I chose to represent data concerning the population density of each county in North Carolina, as well as what percentage of each county's population has a bachelors degree or higher. I was initially curious to use those data sets because I wanted to see how population density correlates with higher level of education.

Dot Density Map

The above map depicts the population density and rough distribution of persons under the age of 18 (also referred to as minors). Each dot represents 400 individuals, with a total of 1,005 dots for the entire map.

Final Map Proposal

Area of Interest: The United States of America

Tpoic: The number of breweries and beer consumed by state. 

Plan: To make a bivariate a chloropleth of the number of breweries per state, and overlay that with a proportional symbol of beer consumption per capita (perhaps beer steins, perhaps kegs).

Data: The wonderful thing about beer is that there's a plethora of data available (such as the brewer's almanac), and data is available for at least the past decade. 

Data resources include:
http://www.beerinstitute.org/assets/uploads/2012_Beer_Consumption_By_State.pdf
http://www.beerinstitute.org/br
http://www.brewersassociation.org/pages/business-tools/craft-brewing-statistics/breweries-per-capita

Audience: Aimed to be utilized by casual beer drinkers and beer enthusiasts alike. 

Isoline Lab

This map is a fictitious isoline display of "smerg" levels in the state of Virginia by part per million concentration. Isoline boundaries were determined by a manual interpolation method, and thus the boundaries are not exact.