[GRASS-user] Performing a Maximum Likelihood Supervised classification with a single band

[Veronica Andreo]

Ciao Umberto,

2015-10-13 10:35 GMT-03:00 umberto.minora <umberto.minora at unimi.it>:

> 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
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.osgeo.org/pipermail/grass-user/attachments/20151013/7aa12616/attachment.html>