[R-sig-Geo] raster[] slow on large rasters

[Michael Sumner]

Try creating it as a single layer brick, does it make a difference?

Cheers, Mike

On Mon, 3 Oct 2016, 08:26 Kenny Bell <kmb56 at berkeley.edu> wrote:

> I am trying to sample points from a large RasterLayer (~100GB if read into
> memory).
>
> raster::sampleRandom relies on raster raster:::.readCellsGDAL which seems
> to loop through rows, read in entire columns using rgdal::getRasterData,
> and subset those columns in R.
>
> Sampling 100000 pts from this raster is only a few per column, so this
> isn't efficient.
>
> Using my own random numbers with `[` also relies on
> raster:::.readCellsGDAL.
>
> Does anyone have a suggestion for a better practice?
>
> The raster is public so this code should be reproducible:
>
> download:
> ftp://ftp.nass.usda.gov/download/res/2015_30m_cdls.zip
>
> cdl <- raster("2015_30m_cdls/2015_30m_cdls.img")
> raster::sampleRandom(cdl, size = 100000) # slow
>
> Cheers,
> Kenny
>
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>
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-- 
Dr. Michael Sumner
Software and Database Engineer
Australian Antarctic Division
203 Channel Highway
Kingston Tasmania 7050 Australia

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