Goldberg, Wilson, and Knoblock (2007) note how geocoding match rates are much higher in urban areas than rural ones. The authors describe two routes for alleviating this problem: geocoding to a less precise level or including additional detail from other sources. However, both these routes result in a “cartographic confounded” dataset where accuracy degrees are a function of location. Matching this idea — where urban areas and areas that have been previously geocoded with additional information are more accurate than previously un-geocoded rural areas — with the idea that geocoding advances to the extent of technological advances and their use, we could state that eventually we’ll be able to geocode everything on Earth with good accuracy. I think of it like digital exploration — there will come a time when everything has been geocoded! Nothing left to geocode! (“Oh, you’re in geography? But the world’s been mapped already”).
More interesting to think about, and what AMac has already touched on, is the cultural differences in wayfinding and address structures. How can we geocode the yellow building past the big tree? How can we geocode description-laden indigenous landscapes with layers of history? Geocoding historical landscapes: how do we quantify the different levels of error involved when we can’t even quantify positional accuracy? These nuanced definitions of the very entities that are being geocoded pose a whole different array of problems to be addressed in the future.