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Center of mass of a SpatialPointsDataFrame object - Which projection?

On Thu, Jun 7, 2012 at 2:10 PM, PCB <pedrocontebarros at gmail.com> wrote:

            
So your data is:

 Lat, Long, Time, Mass
What do you mean by 'each distribution'? Your second sentence makes
me think that Time is discreet, or can be grouped into discreet
'Occasions'.
Your data are samples from an underlying distribution of mass, so you
want to do something like Kriging to get an interpolated surface over
a grid.
If the Kriging package you use (and there's about 4 in R - gstat,
geoR, et al - read the Spatial Task View) can work out distances from
lat-long on the sphere (or ellipsoid) then you don't need to. However
computing distances from lat-long can be slower than from x-y
cartesian coords.. so...

 If your data are over a relatively small area then convert to a
cartesian coordinate system in metres for units and then all the
Kriging packages will work, and they'll compute distances using
Pythagoras.

 Now, which projection? Depends on the region you have data for. UTM
is a fairly safe bet, unless you're close to the poles, in which case
I think there must be polar projections. Check
www.spatialreference.org and see what turns up.
I think most of the Kriging packages can mask the output region by a
polygon, or you can mask raster objects with rasters or clip them to
polygons.
The Spatial Task View is the place to start!

Barry