Working with HIFLD Open Data

I finally had a little time to play with some of the data available through the HIFLD Open site.  For my first pass, I decided to have a little fun by estimating how much of the United States a driver could cover in an electric vehicle while remaining in range of a charging station. For vehice ranges, I used the report ranges in this article: 10 Electric Vehicles With the Best Range in 2015.

electric_app

The process was fairly straightforward:

  1. Download the alternative fueling station data from HIFLD Open.
  2. Using QGIS, query out the electric vehicle charging stations.
  3. Also in QGIS, reproject the data to something suitable for distances. (Thanks, Gretchen!)
  4. Again in QGIS, create a range contour for each vehicle by doing a buffer/dissolve using the reported range values.
  5. Export to GeoJSON and build a web app.

There are some obvious flaws, such as the fact that the buffers represent flat-earth distances. A proper estimate should take terrain into account, at a minimum. This cursory look indicates that a driver make take a pleasant trip up and down the costs and out to the mid-west but, unless that driver is in a Tesla, may have trouble on a cross-country trip. You can feel free to check out the application here. (Oh, and a big shout out to CartoDB for the basemap tiles.)

This application was a quick diversion that just scratches the surface of what can be done with the former HSIP data. Now that the HIFLD data is available, I’m looking forward to seeing what sort of crowd-sourced infrastructure analytics start to appear.