Provided you can convert the format to netcdf, you could use a tool like cdo which does exactly what you want
"CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data." https://code.zmaw.de/projects/cdo/ gdal supports netcdf output, you might have to do some fixing up of the time axes though. Basically I would do - loop on each file: - convert to netcdf - set the time axis with cdo settime <def> - merge all files: cdo mergetime <infiles> outfile.nc - operate on the resulting file with cdo operators (cdo timmean, cdo timmax, etc) Cheers Etienne On Fri, Jul 13, 2012 at 11:01 AM, Knut-Frode Dagestad <[email protected]> wrote: > Hi, > > From a time series of colocated images, I construct a VRT with one band > for each time step using gdalbuildvrt: > >> gdalbuildvrt -separate mtsat.vrt mtsat/*_IR*00.tif > > Are there any tools that can be used to calculate some statistics (min, > max, mean, etc) versus time for each pixel of such a 3D Dataset? > The rasters are large and timeseries long, so reading everything into a > Python NumPy cube is not a good solution. > > Thanks, > Knut-Frode > > _______________________________________________ > gdal-dev mailing list > [email protected] > http://lists.osgeo.org/mailman/listinfo/gdal-dev _______________________________________________ gdal-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/gdal-dev
