Andrea Moed <[EMAIL PROTECTED]> wrote:
I have an existing collection of lat/lons, each representing a place where a photo was taken. I want to computationally find the geographic clusters in this collection, i.e. the geographic areas with the densest concentrations of points. (So it sounds like Andrew's "location-closeness clustering" is what I'm thinking of.) Having found these most-photographed areas, I want to find the geographic name that best describes each area, such as a region, city, neighborhood or park name. So, I'm looking for two different things, a location-closeness clustering algorithm and a gazetteer lookup. Sorry to be confusing.
No problem - just lots of cool problems to be solved with your general problem statement ;) Your project sounds very similar to recreating the Flickr YMap interface? Here is a Javascript (works w/ gmaps) clustering algorithm that works very well: http://www.acme.com/javascript/#Clusterer the code could fairly easily be adapted to server-side computation and storing in a database in bins - though that precludes "dynamic" clustering depending on Zoom level. Then for naming the area - using something like Geonames Reverse Geocoding: http://www.geonames.org/maps/reverse-geocoder.html Does that help? Andrew -- Andrew Turner [EMAIL PROTECTED] 42.4266N x 83.4931W http://highearthorbit.com Northville, Michigan, USA _______________________________________________ Geowanking mailing list [email protected] http://lists.burri.to/mailman/listinfo/geowanking
