Don't use UTM for anything with a longitude extent greater than about 6
degrees, this is the basis of a UTM zone. I think it's a poor choice in
general unless you need to work with a local authority using it. Mercator
is for straight line compass trajectories and the need for that is not as
great as it once was. UTM reflects a time where that property was very
important for navigation, then an easy to calculate projection was tipped
on its side to work for for small local regions in a narrow longitudinal
band.  Choose a local equal area projection, such Lambert Azimuthal Equal
Area "laea", they are easy to define with PROJ.4 and easy to transform
from/to anyway as long as you record the details.

Cheers, Mike


On Monday, June 11, 2012, PCB wrote:

> Yes, in this case I have one set of observations per year, so Time is
> discreet.
>
> I did look at the Spatial Task View, but could not understand all that I
> read...
> I am using the gstat package, looks like it has all the features I want,
> but
> I still need to find out how to calculate the distances if I am using a
> lon-lat CRS. Anyway, I will try a go at using UTM, and will get back to the
> Spatial Task View. I am looking at an area between -5 and -25 Degrees, with
> a longitudinal extent of about 15 degrees longitude
> Since we are at this, is gstat the most appropriate package for doing this?
> or should I be trying one of the others? I am trying to work also with the
> "raster" package, for doing the cropping, but your mail suggests I could do
> it using gstat. I will find out how to do it there.
> Thanks a lot
>
> .
> Barry Rowlingson wrote
> >
> > On Thu, Jun 7, 2012 at 2:10 PM, PCB &lt;pedrocontebarros@&gt; wrote:
> >
> >> I have a dataset that represents measurements of fish density at a
> number
> >> of
> >> sampling locations at sea, in several different occasions (the sampling
> >> locations are not always the same), stored as a a list of
> >> SpatialPointsDataFrame objects.
> >
> >  So your data is:
> >
> >  Lat, Long, Time, Mass
> >
> >> I want to calculate the center of mass of each distribution, to describe
> >> whether there is a trend in the overall distribution of the fish.
> >
> >  What do you mean by 'each distribution'? Your second sentence makes
> > me think that Time is discreet, or can be grouped into discreet
> > 'Occasions'.
> >
> >> I have three main questions:
> >> a) Should I use the original points for calculating the centre of mass,
> >> or
> >> should I interpolate them first to a grid? I assume doing it on the
> >> original
> >> points will make the result dependent on the location of these points,
> >> that
> >> is really not linked to the underlying fish distribution
> >
> >  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.
> >
> >> b) Should I reproject the data before calculating the center of mass
> >> (they
> >> are in lon-lat). If so, which projection should I use?
> >
> >  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.
> >
> >
> >> c) A rectangular grid will include many locations on land, where no fish
> >> could have been recorded anyway. How do I get a grid I can use to
> >> meaningfully calculate the center of mass?
> >
> >  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.
> >
> >> Thanks for your time, and any pointers will be highly appreciated.
> >
> >  The Spatial Task View is the place to start!
> >
> > Barry
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo@
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
>
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> Sent from the R-sig-geo mailing list archive at Nabble.com.
>
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-- 
Michael Sumner
Hobart, Australia
e-mail: mdsumner@gmail.com

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