GIS at Dickinson College

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Month: December 2012

The Presidential Election in Terms of Unemployment and Population Density

Fall 2012 presentation by Kendall Beals, David Cruz, Annie Dyroff, Elic Weitzel


In the last eight years, unemployment has become a prominent issue in the U.S. There is also a heavy emphasis on unemployment as it relates to the political sphere, and in particular the presidential elections. With the constant bombardment of statistics put forth in the news and media, it is often difficult to understand the true connections between unemployment and voting trends. This project focuses on gaining a spatial understanding of unemployment as it relates to population density and voting trends. We were interested in identifying whether there is a trend between unemployment and election returns of 2008 and 2011, and whether this is influenced by living in an urban or rural area.


Unemployment data for both years was obtained from the Bureau of Labor Statistics. Population density data was obtained from the US Census Bureau. Presidential Election data was obtained from The Guardian ( Basic county data was obtained from ESRI.


All data was done by county and projected with Albers Conical Equal Area, GCS 1983. Unemployment data was based on the percent of people in the civilian labor force that were unemployed. Change in unemployment was determined by calculating percent change in unemployment for each county from 2008 to 2011. Election returns were sorted by the percentage of votes President Obama received in each county. Population density data was analyzed on the basis of prior classifications as to the number of people in each county that lived in a “urban classified” or “rural classified” area of the county.


This map shows a clear pattern of the central part of the US as containing the most amount of urban areas, with the coastal areas being more populated.

This shows the percent of the population that is unemployed in each county in the United States.  Over the whole United States, the unemployment rate ranged from 1.3-32.0%.  While there is a large range in unemployment, the majority of counties fell within the 1.3-8.9% unemployment range with the average being 5.28%.  By analyzing the map visually, one can see that the Midwest region of the United states appears to have a fairly low unemployment rate compared with the coastal areas of the united states such as California, and the New England States.

There is a clear pattern of the central part of the U.S. voting republican. These areas also align with being the most rural areas of the country. In contrast, areas along the coast tended to vote more democratic. These areas also tend to more urbanized.

This shows that majority of the country has roughly a 1.3 to 10% unemployment. There is a distinct area in the midwest with low unemployment. Other than actually having jobs, this can be due to large amount of farmland or land with low population in those counties.

This map shows the election results for the Romney(Red) vs Obama(Blue) Election. This map shows that most of the coastal areas as well as major cities tended to vote more democratic. The midwest as well as most of central united states showed more diversity in votes and are leaning more to vote Republican.

This shows the change in unemployment in the United State from 2008 to 2011.  The unemployment percentages only range from -0.603-1.78%.  The range is very small because this map shows the percent change in the unemployment percentages for each county.  By visually assessing the map, it appears as though most of the country has had at least some increase in unemployment.  However, the upper middle portion of the United States appears to be a concentration of low unemployment increase.  Looking at the metadata for the counties 3 out of the four counties with the lowest increase in unemployment were all located in North Dakota.  These counties were all located in the area that appeared to be very low in unemployment increase.  Another visual observation about the data is that there is a concentration of high unemployment increase in the area coving most of Utah, Wyoming, and Idaho.

This map shows a selected set of counties with a high percent change in unemployment between 2008 and 2011 (greater than 0.85%) and a high rural population (greater than 95%).  The majority of the counties meeting both of these requirements voted for Romney in the 2012 election (91% for Romney, 9% for Obama).  These results appear to be quite significant.

This map shows a selected set of counties with a high percent change in unemployment between 2008 and 2011 (greater than 0.85%) and a high urban population (greater than 80%).  The majority of the counties meeting both of these requirements voted for Romney in the 2012 election (65% for Romney, 35% for Obama).  These results appear to be quite significant and show a trend contrary to common perceptions about the voting tendencies of urban areas.  It would appear based on this selected data set that a high increase in unemployment had more sway over voters than living in an urban area.


From our analyses, we can deduce much about unemployment and how it relates to population density and voting results. It is interesting that unemployment increased less than two percent for all counties. Unemployment was found to be higher in more urban areas, which are also predominantly democratic-leaning counties. Low unemployment was more common in rural areas, which are also predominantly republican-leaning counties. However, it was interesting to note that there was a slight increase in unemployment in republican-leaning counties from 2008 to 2011. The trends that we can take away from this are that low unemployment correlates with more likely to vote republican and urban tends to be more likely to vote democratic. Also, areas with a significant increase in unemployment are more likely to vote republican.


Map Jokes

Need a break from working on final map projects?  Check out these amusing (and very corny) map jokes from!

  • What is the tidiest element on a map? The neatline.
  • Why are maps like fish? They both have scales.
  • Why do paper maps never win at poker?  Because they always fold.
  • What do you get when you cross a cowboy with a mapmaker?  A cow-tographer.
  • What did the mapmaker send his sweetheart on Valentine’s Day?  A dozen compass roses.
  • Why does west longitude need to be cheered up?  Because it is always negative.
  • Why did the dot go to college?  Because it wanted to be a graduated symbol.
  • What do you call a map of outhouses in the woods?  A shaded relief map.
  • What do you call a USGS quadrangle with green water, blue forests, and all the names spelled backwards?  A topo-illogical map.
  • What kind of maps do spiders make?  Web-based maps.
  • What projection do lost sheep use to find their way home?  The Lamb-ert Conic Conformal projection.

Driving Distances Associated with CSA Food Distribution

Claire Persichetti, Spring 2012

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