Acacia:

The use case you are talking about (resampling categorical data) is a
complicated one, but I provide a solution to it in my spatial.tools package
via the projectRaster_rigorous function (now up on CRAN or on R-forge, make
sure you have version 1.2.1 or later).  I am not sure any of those other
programs have what you are talking about available.

Please be aware that projectRaster_rigorous is an intensive calculation (we
have to essentially vectorize each of the input cells, reproject them, clip
them to the new output boundary, and figure out which one has the highest
aerial coverage), so I would recommend running the function in parallel
(use sfQuickInit(cpus=X) where X is the number of cores you have on your
local machine).  3 hours seems about right for a large file (although the
parallel processing should bring it down somewhat).

--j


On Fri, Nov 1, 2013 at 1:10 PM, Acacia dealbata
<noelia.gonzalezm@gmail.com>wrote:

> Hi Loic!
> Thanks for your answer. I am working on it, but the problem is that I am
> not
> able to finish the first step (aggregate), as it takes hours (3 hours by
> now
> and not finished). I am not sure if it is due to the aggregate code or to a
> problem in the original map... I think I am going to make some proofs with
> Quantum SIG and GRASS...
>
>
>
> --
> View this message in context:
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> Sent from the R-sig-geo mailing list archive at Nabble.com.
>
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-- 
Jonathan A. Greenberg, PhD
Assistant Professor
Global Environmental Analysis and Remote Sensing (GEARS) Laboratory
Department of Geography and Geographic Information Science
University of Illinois at Urbana-Champaign
259 Computing Applications Building, MC-150
605 East Springfield Avenue
Champaign, IL  61820-6371
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