A package for spatial data classes: request for comments

As I mentioned to Roger Bivand a few days ago, it might be a good
idea to take a look at the spatial classes in ESRI's ArcGIS. In my
view they are not 100% ready for statistical analysis, but the vector
classes are very well structured. 

Luc, are you referring to the "Geometry" section in the second paper
(arcob81post.pdf) of the incredibly hart to read poster at

http://www.esri.com/library/whitepapers/ao_lit.html
or is there some more accessible information to these classes?

What is missing is an efficient
way to incorporate "topology" (contiguity structure) to provide
an easy way to construct spatial weights. In GeoDa, we build this
from scratch, using the shape files, but  that's not the way it
should be (although very fast).

If constructing it is very fast, why should we incorporate it in the
class definition, instead of creating it on the fly? Package gstat
builds PR bucket quadtrees for fast neighbourhood selections,
which makes the program scalable to large interpolation or
simulation jobs, but it never stores them.
We recently found out that if you want to apply
gstat to say 1e9 points (so many that you will never be able to
hold them in RAM), even then quadtree _building_ does take so
little time (minutes, maybe) that it does not reward storing it.

When constructing topology from prohibitively large spatial data
bases in R, another route to investigate would be Postgress/PostGIS;
It can deal with tree search indexes, and I think it uses the GEOS
geometry toolkit.
--
Edzer