Ciao Umberto, 2015-10-13 10:35 GMT-03:00 umberto.minora <[email protected]>:
> Ciao Veronica, > > thanks for the hint and sorry for the late feedback. > I'd like to use GRASS so I might go for the "r.texture" solution. Anyway, > I did not get how to use it for my scope. > What r.texture does is to extract different texture measures from a raster map, creating several other raster maps that you can then use as extra information (derived from the original map) for the classification. First of all, as I already have training areas, i want to use them in a > Supervised classification rather than an unsupervised one (as ISODATA). > Second, I am only interested in using one band for the classification, > which was the reason I could not use "i.maxlik". > Now, as I understand, using "r.texture" will generate images with textural > features from my single band raster map. I got that I could use these as > the needed input for the "i.maxlik", but I did not get what "r.texture" > will give me, and if that is going to be a good statistic sample for the > Supervised. > Well, I don't know either :) That will depend on the image, it's resolution, and the features of the area you are studying, i guess... I'm afraid you will have to try... :P > Moreover, which method would you suggest? > I am pretty new to this function, so I hope you (or anyone else) could > give me a hand to better understand it. > Thanks in advance! > I haven't done myself a classification in GRASS, but here is a nice tutorial you may start with: https://grasswiki.osgeo.org/wiki/Image_classification Cheers, Vero
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