Reverse geocoding is hard

Thank you! I appreciate that :-)

It's a lot more expensive, but measuring navigation distance rather than straight line distance would avoid the "river" issue. Although depending on the routing engine and dataset it might well introduce more issues where points can be really close on foot but the only known route is a driving route.

Most people don’t have an intuitive sense of just how technically difficult mapping from real geospatial coordinates to feature spaces is. This is a great example of a relatively simple case. You are essentially doing inference on a sparse data model with complex local non-linearities throughout. If you add in dynamic relationships, like things that move in space, it becomes another order of magnitude worse. We frequently don’t have enough data to make a reliable inference even in theory and you need a way of reliably determining that.

This problem has been the subject of intense interest by the defense research community for decades. It has been conjectured to be an AI-complete type problem for at least ten years, i.e. solving it is equivalent to solving AGI. The current crop of LLM type AI persistently fails at this class of problems, which is one of the arguments for why LLM tech can’t lead to true AGI.