Lab number 2 is designed to increase knowledge in regards to downloading and mapping data sets acquired from the United States Census Bureau. The Census Bureau provides a variety of collected data in order to adapt policies, distribute funds, and apply Congressional seat proportions. Census data comes in two formats, SF1 and ACS. SF1 data is gathered in ten year increments and counts total population and the distribution of the population in the United States. ACS data is now gathered on a yearly basis and provides more detailed information on the population, including employment, ethnicity, economic, and educational characteristics. Using this data to determine the total population by counties as well as percent of households with a member over the age of 65 by county will be the final objective of this lab.
Methods:
To begin, access to the Census Bureau website at http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml and it will provide data to be downloaded for the map. Once a topic is chosen it is important to determine the geography of where the desired resulting map is intended, in this case each county within the state of Wisconsin. Once the data for the correct location is downloaded in a zip file, the user will need to locate the file and unzip it. The unzipped table with the necessary data needs to also be converted to an Excel file so it can be imported to ARCMap.
This download only gives us raw data. To display it geographically, we need to also download a shapefile that will provide a spacial reference for the data mapping. This is done by viewing the Map tab within the Geography section of the Bureau website. A download and another unzip is necessary for the shapefile.
With the files downloaded in an ARCMap connected folder, dragging the shapefile and Excel file into a blank map will not map the data to the spatial reference. To fix this, it is necessary to join the files using a common attribute. We wish to join the Excel table to the shapefile, so clicking the join option from the shapefile will allow for this. Next join the files by their common attribute and double check the shapefiles attribute table to confirm the join was successful.
Next the data can be mapped. Since total population is an entire statistic, it does not need to be normalized, but the second example of this map where we are looking at the amount of households with a member 65 years of age or above will require normalization versus the total amount of households. This is all done by right clicking the shapefiles and creating a map in the symbology tab of the of the properties option. Also within the symbology tab it is important to clean up numbers in labels and determine a proper break point method to provide a reasonable picture.
Once the maps are created, the user will need to switch to layout view to edit and make the map appealing from a cartographic stand point. Using grids, rulers, and snap points, both maps were lined up side by side. To ensure both pictures of Wisconsin are not distorted, the data frames should have a state projection that can be observed and changed by right clicking each data frame and choosing the properties option. To ensure equal sizes, find the right size on one state and copy the scale to the other. Additional features to make the map more appealing include adding a title, legends, scale bars, north arrows, author, the source, and if desired, a basemap. In this exercise, it is more efficient to also be in landscape view versus portrait to line the maps side by side.
Results:
The result of these methods will provide two side by side, equally sized respresentations of Wisconsin and the individual counties. Using the legend, it is apparent from the left hand picture that population density is heaviest in Southeastern Wisconsin, but based on the right hand picture, it also appears to be somewhat younger (Figure 1). For example, the selected county in Figure 2 shows that it has one of the highest percentages of households with a member 65 years or older, but is also the third lowest populated county.
Figure 2. Iron County
Sources:
U.S. Census Bureau. (2010). Retrieved from
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
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