In Transitland v1, we manually curated a list of a single headquarters city or most important city for each transit operator.
In Transitland v2, we've replaced manual curation with an automated process. While it's inexact, the automated process enables browsing Transitland operators by places across the world and places data in the REST API endpoints for agencies and operators.
The place-matching process uses geographic datasets of populated places around the world and labels transit agencies based on which of those populated places are nearby to the transit agency's stop locations. Each place-match is assigned a score. An operator may have more than one place-match, in which case the place-matches are sorted by score.
Currently, Transitland's place-matching process uses the following 1:10m cultural vector layers from the Natural Earth project:
- Admin 1 – States, Provinces (
- Populated Places (
We know this is coarser than some US-based users are interested in. In the future, Transitland may link American agencies to US Census geographies to get the precision that planners in the US may be interested in.