GEOG 486
Cartography and Visualization

Create a Multivariate Map


This project will be conducted differently from those that have led up to this lesson. For this project, I will give you a dataset that is fairly ready to be worked with cartographically, and your task is to create a multivariate map (or a layout that incorporates information graphics).

You will be working with FAA Birdstrike data for 2010. The FAA keeps detailed records of every reported birdstrike in the United States (or involving a US-registered aircraft outside the U.S.), and they recently made their entire database publicly available. The original dataset includes over 129,000 individual records, covering a time period from 1990 to 2011, associated with airport codes. Because the dataset is so complex, I created a version that is drastically simpler for you to work with containing birdstrike incidents aggregated by month to airport point locations. Your goal is to create a multivariate map that visually represents this monthly data across the U.S.

A. Download Lesson Data (28.74 MB)

The Lesson_8 folder contains a map document (.mxd file) to get you started, and a folder titled Birdstrike_Data.  Inside the Birdstrike_Data folder are two geodatabases, one containing basemap data and another containing the FAA birdstrike data, and an excel file titled read_me (though you don't really need to read that file unless you get into working with the original birdstrike data). 

B. Open the .mxd

  • Open the Birdstrike_Start.mxd file to get started with this dataset.

Inside you will see a layer birdstrike_2010_bymonth. This contains the birdstrike data aggregated to airport points. And you will also see three basemap layers (and there are others in the basemap geodatabase if needed).

  • Open the attribute table of the birdstrike_2010_bymonth layer. 

Take note of the few attributes associated with the birdstrike data. They are limited to airport description, name, latitude and longitude, 12 fields for the 12 months of the year, and a field titled all_2010.

The fields for each month contain data on the frequency of birdstrikes that month for each airport, and the field titled all_2010 contains the frequency of birdstrikes for each airport for the entire year of 2010.

C. Create a multivariate map showing the variation in birdstrikes at airports over the 12 months of 2010

How you do this, I leave up to you. But below are a couple suggestions, tasks or guidelines for the final map:

  • The map can use multivariate symbols, or can show multiple layered univariate symbols, or you could create a series of small multiples (on one layout), or you could incorporate information graphics (other than maps) into the layout. In the next section I provide some examples, but I strongly recommend that you look for examples on your own.
  • Focus on the U.S. There is some unplotted/unknown data in there, and some data overseas, so it is OK to not use data if it doesn't fit your purpose, is outside of your extent, or even skews your focus. 
  • Use an appropriate projection for the area you are mapping. The .mxd comes with the data projected in the Robinson world projection. This is not the projection you should have the data in if mapping the U.S.
  • You can edit the data if you want, e.g. create new fields based on seasons, or aggregate data to the states, etc. and map that instead of individual months.
  • Only use base data if it is useful for the purpose of the map. For instance, you probably won't need rivers, roads or lakes - except you very well might want the Great Lakes so the U.S. boundary looks correct. Create a data layer from the lakes layer that just contains the Great Lakes.
  • Try to stick to an 8.5" x 11" layout. 
  • Ask questions

D. Example multivariate maps, multivariate symbols and small multiples

Below are several examples just to open up ideas. Your map does not have to look like these, but if you attempt any of the symbols or ideas in these maps, or if they spur similar symbols, that is good, too.

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Figure 8.1.1 This map uses a custom multivariate symbol that incorporates data for count and time of year. Explore the zoomable version of this map to see the multivariate symbols up close.
Credit: Good Infographics
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Figure 8.1.2 This multivariate symbol (not on a map) also shows data for counts by month, but with proportional wedges within each symbol. More examples of rose charts can be seen at the blog
Credit: Zachary Forest Johnson

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Figure 8.1.3 This example is from a previous student who mapped unrest in the Middle East. She created a multivariate symbol (inspired somewhat from the Occupy map show above) that also incorporates monthly attribute data, this time via a color scheme in linear static squares. Here is the PDF version/Arab Spring for a closer look.
Credit: Michaela Mesquite
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Figure 8.1.4 This is another student example that I suspect would work well for this data, i.e. proportionally sizing symbols based on total value for each location. The symbols themselves show proportions or values of individual attributes. (Another option similar to this could be bar charts or segmented bars as symbols.)
Credit: Andrew Milson

If you are considering small multiples, consider the Figure 8.1.5, below (and also think back to the 2nd layout from our Lesson 4 assignment), where the focus of the design is on the symbol for the data variable (not on the base data or changes in the legend or other features). Repetition and similarity are key here.

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Figure 8.1.5 The above example, mapping areas of moderate to extreme drought from 1899 to 2012, illustrates how small multiples can effectively communicate temporal data if design is focused on the data, not the background map and marginal info. The New York Times
Credit: NYTimes

That is it for the instructions for Lesson 8. See the Final Tasks page to see what is due for this lesson.

If you have any questions, please post them to the Lesson 8 Discussion Forum.