I have data sets that contain, among many features, GPS coordinates (latitude and longitude). I'd like to use these data sets to explore problems such as: (1) computing ETA to drive between start and end points; and (2) estimating the amount of crime for a specific point.

I'd like to use a linear regression model. **However, can I use these GPS coordinates directly in a linear model?**

Latitude and longitude do not have an [ordinal property][1], such as with a person's age. For example, the two points (40.805996, -96.681473) and (41.226682, -95.986587) do not seem to have any meaningful ordering. They are just points in space. I was thinking of replacing them with categorical US zip codes and then doing [one-hot encoding][2], but that would result in **a lot** of variables.


  [1]: https://stackoverflow.com/questions/34078894/categorical-and-ordinal-feature-data-difference-in-regression-analysis
  [2]: https://www.quora.com/What-is-one-hot-encoding-and-when-is-it-used-in-data-science