Been attempting (with no success so far) to implement the random forest classification in ArcMap on a reasonably large image. If I throw a raster with say 20-30 bands in it, works fine, just takes time. However my aim is really to get the tool to classify a 250-band raster, to really see how well it works on our data. Splitting the 250-band raster into multiple smaller band rasters defeats the purpose of what we're trying to achieve.
However this means our input raster (ESRI GRID stack format) is over 80Gb in size, and ArcGIS can't seem to handle it. So I am basically wondering if anyone has actually managed to implement any of the image classification tools on relatively large rasters? If not, is anyone aware of what the practical limitations of these tools are?
I have access to both Desktop 10.7 and Pro, run into problems with the large rasters on both and am running a desktop PC with decent specs.
Out of frustration, I have also tried to implement random forests using just a python script outside of the ESRI environment on a TIFF version of the GRID stack. Code works fine on small'ish inputs, but computer said "no" for the big files (the TIFF file is nearly 70 times the size of the GRID stack...).
Any advice? No access to a supercomputer at the moment, but if that's your advice, and you've successfully got it to work on one, happy to hear about it!