At the end of my Intro to GIS course in grad school, I ran into a problem. The professor assigned us a term project where we were to choose a spatial data set and perform some kind of analysis upon it. Unfortunately for me, this assumed we were all in fields that were already working with spatial data; economists, sociologists, marine biologists, and so on. As a humble code monkey, I had no topical data to work with.
I was soon made aware of Tyler Vigen’s Spurious Correlations, a website that draws correlations between (hopefully) unrelated data sets, such as the divorce rate in Maine and margarine sales per capita over time. There is a wealth of freely available spatial data made available by government agencies and ESRI, so I thought it would be funny to try out similar techniques with these data sets.
These are my results.
Eagles and K-Cups
With the exception of Washington County, eagles seem to make their homes in areas where household K-Cup ownership is at or higher than the national average.
Schools and Aquifers
589 of Maine’s 795 schools are within 3 km of an aquifer. This means that if you are at a school, there is a 74% chance that you are within walking distance of a significant source of groundwater.
U.S. Cellular Coverage and Oil Spill Hotspots
US Cellular offers great coverage in areas where hazardous oil spills occur the most.
Cemeteries and Broadband Coverage
3875 of Maine’s 3929 cemeteries are located exactly within broadband coverage areas (98.63%).
Red Cross Facilities and Bedrock Formation Eras
In what I can only consider to be a deliberate move, Red Cross has built their facilities in Maine on top of bedrock formed before the Devonian era. This means that if you got into a time machine and went back to the period at which the bedrock was formed beneath any Red Cross facility, you would not find sharks, ferns, trees, insects, or land vertebrates.
These datasets are in no way scientifically rigorous.