Roongpiboonsopit and Karimi’s 2010 comparison study of five free online geocoders is an example of an important process in weeding out poor geocoders and creating one that works accurately and reliably. Considering geocoding is at the heart of many GIS applications, especially those involving the Geoweb, spatial accuracy is key. The authors used empirical analysis to determine the “best” geocoders based on accuracy and a number of other metrics. They concluded that Google, MapPoint (Microsoft) and Yahoo! are all quite effective, while Geocoder.us and MapQuest are less so.
In thinking about geocoding and the development aspects of the geocoding process, I realized that geocoding development is much like development in other topics we’ve covered, such as LBS and AR. As all of these progress and become more accurate and lifelike, they are approaching a level of artificial intelligence that is simultaneously creepy and cool. For instance, if a geocoder like Google’s uses all of the information it already has on us, there will not be any need for formal geographic indicators like street address, coordinates, or even official place names. If the reference database were to include our own vernacular and preferences along with the official names and spatial reference algorithms, then simply typing or saying “home” would pinpoint our location on a map quickly and easily. This isn’t even about spatial accuracy anymore, but rather “mental” accuracy. Perhaps I’m getting ahead of myself, but I see the possibilities with geocoding not just in terms of developing a usable application for plotting points on a map, but also in terms of expanding how we think of space (ontologies) and how we conceptualize our environment (cognition). Integrating new tools into the pre-existing algorithms has and will continue to change how we live our lives.
– JMonterey
Tags: geocoding, GEOG 506, Karimi, Roongpiboonsopit