<br>Another option you may want to check out is GRASS GIS 7.0 (the RC1 just got released a day ago, but it is rock solid, very fast especially on rasters, and able to deal with very large raster layers. It has a bit of a learning curve, but once you get the basics it offers easy scripting in shell or python. And you can access it through QGIS (processing toolbox).<div><br></div><div><br><div class="gmail_quote">On Fri Jan 16 2015 at 6:12:52 AM Prasun Kumar Gupta <<a href="mailto:prasunkgupta@gmail.com">prasunkgupta@gmail.com</a>> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div>Hi Nicolas,<br></div>I work with lots of *very* large rasters.<br></div>Here are my thoughts on doing geoprocessing with them on Windows environment.<br></div><div>The steps are in increasing order of speed and user/coding complexity.<br><br></div><div>1. QGIS front-end generally tends to hang when dealing with large rasters. <br></div><div>R is said to be slow [1]. [1] also suggests that you use ORFEO's toolbox [4]<br>It is recommended that you try the Python program gdal_calc.py<br></div><div>You may explore compression options [2]<br></div><div><br></div>2. I would personally opt for the IDL [3] programming language. The compiler is, however, not free.<br><div>It is really fast and powerful for array intensive operations.<br><br>3. Multi-threaded / Parallel / GPU programming may help. However it has a steep learning curve (atleast for me).<br></div><div>This presentation [5] in FOSS4G PDX 2014 on "Fast Big Data? A High-Performance System for Creating Global Satellite Image Time Series"<br>was very informative and used HDF data cubes and GDAL to solve the problem.<br><br></div><div>I hope you have got some useful pointers.<br><br></div><div>Regards,<br></div><div>Prasun<br><br></div><br>[1] <a href="http://gis.stackexchange.com/questions/88996/per-pixel-statistical-calculations-on-a-raster-stack-using-gdal" target="_blank">http://gis.stackexchange.com/questions/88996/per-pixel-statistical-calculations-on-a-raster-stack-using-gdal</a><br>[2] <a href="http://gis.stackexchange.com/questions/69462/gdal-calc-py-outputs-huge-files" target="_blank">http://gis.stackexchange.com/questions/69462/gdal-calc-py-outputs-huge-files</a><br>[3] <a href="https://en.wikipedia.org/wiki/IDL_%28programming_language%29" target="_blank">https://en.wikipedia.org/wiki/IDL_%28programming_language%29</a><br>[4] <a href="http://orfeo-toolbox.org/Applications/BandMath.html" target="_blank">http://orfeo-toolbox.org/Applications/BandMath.html</a><br>[5] <a href="http://vimeo.com/107532162" target="_blank">http://vimeo.com/107532162</a><br><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Jan 15, 2015 at 9:38 PM, Nicolas Cadieux <span dir="ltr"><<a href="mailto:nicolas.cadieux@archeotec.ca" target="_blank">nicolas.cadieux@archeotec.ca</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi,<br>
<br>
In the next few weeks, I will be trying to do some Raster Math on some very large Rasters. Rasters will likely be too large for the system memory (72Go). I will have a PCIe solid state drive to help out.<br>
<br>
Does anyone know how QGIS will manage? Can we use the raster calculator without loading the files into memory? Can the Python api solve this problem?<br>
<br>
Doing the math on subsets of the data could help but I still need to process the entire extent at some point to get to the raster statistics.<br>
<br>
I know I can use the R Raster package to do it but that package is not flexible when dealing with grids with different resolutions. <br>
<br>
Any thoughts on this would be appreciated.<br>
<br>
Thanks<br>
<br>
Nicolas Cadieux M.Sc.<br>
Les Entreprises Archéotec inc. <br>
8548, rue Saint-Denis Montréal H2P 2H2<br>
Téléphone: 514.381.5112 Fax: 514.381.4995<br>
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