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Ciao Veronica,<br>
<br>
thanks for the hint and sorry for the late feedback.<br>
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.<br>
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).<br>
Second, I am only interested in using one band for the
classification, which was the reason I could not use "i.maxlik".<br>
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. Moreover, which method would
you suggest?<br>
I am pretty new to this function, so I hope you (or anyone else)
could give me a hand to better understand it.<br>
Thanks in advance!<br>
<br>
<div class="moz-cite-prefix">Il 08/10/2015 22:21, Veronica Andreo ha
scritto:<br>
</div>
<blockquote
cite="mid:CAAMki4H26B5PmeFPMxHD-F9z3EFQ86BJq22+pNqfQv+sB72nJA@mail.gmail.com"
type="cite">
<div dir="ltr">Ciao Nikos :)
<div><br>
</div>
<div>Yes, you are right! I missed that one!</div>
<div><br>
</div>
<div>There's ISODATA unsupervised classification algorithm (not
in GRASS that I know) and it allows for just one band input.</div>
<div><br>
</div>
<div>Cheers, </div>
<div>Vero</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">2015-10-08 16:52 GMT-03:00 Nikos
Alexandris <span dir="ltr"><<a moz-do-not-send="true"
href="mailto:nik@nikosalexandris.net" target="_blank">nik@nikosalexandris.net</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">* Veronica
Andreo:<br>
<span class=""><br>
> Ciao Umberto,<br>
><br>
> AFAIK, classification is multivariate on its
statistical basis, so that's<br>
> why it will only take a group as input. If you only
have one band, you may<br>
> want to extract some information from it, for example
by using r.texture<br>
> module [1]. With those resulting new bands and the
original one you can<br>
> create then a group and perform the classification
you prefer.<br>
</span>> [1] <a moz-do-not-send="true"
href="https://grass.osgeo.org/grass71/manuals/r.texture.html"
rel="noreferrer" target="_blank">https://grass.osgeo.org/grass71/manuals/r.texture.html</a><br>
<br>
<br>
Ciao Vero. There is, for example, the ISODATA algorithm out
there.<br>
Just not in GRASS (yet?).<br>
<span class="HOEnZb"><font color="#888888"><br>
Nikos<br>
</font></span></blockquote>
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