Dear Matias Thanks for the thought. Any help is always appreciated.
I actually am using this agglomeration (when I eventually derive it ;-) ) to seed kmedoids or kmean centroids for statistical clustering, (doing it in R via a variety of methods to see what works best). I already have a much larger set of points that need to be clustered around the set of centroids I generate from this grid agglomeration process.
However doing this gridding and agglomeration process first gives me a twofold advantage, in that it not only gives me the centroid for the clustering of the "other" data set, but also allows me to identify the actual spatial areas in which some of my (statistical) cluster points (in the other data set) should fall to start with, so I will do at least one level of spatial intersection, then one level of statistical clustering on top.
I am at this point favoring doing the grid agglomeration programmatically - perhaps I can get that done today. (Unless anyone comes up with an SQL solution before I finish coding it up ;-))
I'll let you folks know if I make the programmatic approach work but I'm still open to other input in the meantime.
Thanks to all for suggestions thus far. Kind regards Derek. _______________________________________________ postgis-users mailing list [email protected] http://postgis.refractions.net/mailman/listinfo/postgis-users
