Cartographic Skills Final Project

Our final project was designed to take a semester's worth of learning to create a final map for this course. The objective was to take on the role of someone working at the U.S. Department of Education and create a map of 2013 mean SAT (or ACT) scores by state and the participation rate of high school graduates, with the idea that it would be published in the Washington Post.

We were to obtain a basemap from an outside source and apply a suitable projection to that basemap. We had to input the SAT data into Excel and import the tabular data into ArcMap. We wanted to present two datasets on one map (participation rate and test scores) and classify and symbolize the data in a way that easily communicates the information.

For this project, I chose to use SAT data from the U.S. Census Bureau. I downloaded the basemap (also from the U.S. Census Bureau) and projected it into the Albers Conical Equal Area projection. I initially had problems with my scale bar due to this, as I initially defined the projection before adding the data. When I restarted the project and added the data first, the scale bar problem was no longer present. After creating the Excel file, I added the data table and joined it with the states shapefile using the Joins and Relates tool, making sure to only use matching records (there were a lot of "null" values when I selected the other option). Once they were joined, I could go about making some map decisions. First, I wanted to display the participation rate as a choropleth map, which is appropriate here because the values of the participation rate change abruptly at enumeration boundaries (in this case, the state boundaries). I chose a color scheme that was suitable, using light colors for smaller values and darker colors for higher values. I used the natural breaks classification scheme because it was showing the data well and was keeping like values mainly clustered together in the same class. The natural breaks method minimizes the variance within classes and maximizes the variance between classes, which I think works well with this dataset. To display the second data set, I copied the original state/tabular data joined layer and overlaid it on top of the first one. Using this second layer, I could symbolize the SAT scores and still be able to see the choropleth map of participation rates. For this data, I decided to use graduated symbols and a natural breaks classification scheme. The graduated symbols allow the map reader to easily understand the information being provided and I felt displayed the information the best; small circles represent lower mean test scores and larger circles represent higher test scores, which is an intuitive way of displaying the data. Again, I used the natural breaks classification scheme to keep the range within each class fairly uniform and to keep like values within a specific class as much as possible. I used a total of 5 classes for both sets of data. For the choropleth map, if there were many more classes the color variation would be so small that you would have trouble distinguishing between them. With the graduated symbols, 5 classes seemed to be the right amount to display the data, and I didn't want my symbols to become too small or too large. Once I decided on the symbology and classification, I inserted my legend and scale bar, labeled the states and exported the map to finish on CorelDraw.

Most of the work I did on CorelDraw was moving things around to make the map look neat and professional. I arranged things so that the graduated symbol and the state label were not overlapping either each other or a state boundary. Sometimes this meant I needed to place the label and/or symbol off to the side and draw a line to the map. To stretch the map some without stretching the symbology, I placed the graduated symbols into their own layer separate from the map. I also made sure to stretch the scale bar with the map since I imported it and wanted it to remain accurate. I resized both Alaska and Hawaii and created an inset of using CorelDraw and the drawing features, noting that they are not to scale. Finally, I added the essential elements (title, data source, who created it) and used an effective background color that emphasizes the map.

I really enjoyed making this map, once my issues with the proper projection were sorted out. I liked that it took everything we've learned this semester from towards the beginning (data classification and symbology) to more recently (joining tabular data). This course has taught me that a lot of thought into what story I'm trying to tell is important in creating an effective map. I really enjoyed this course and I hope to take what I learned here into my endeavors in the future.