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

[Nikos Alexandris]

* Umberto Filippo Minora <umberto.minora at unimi.it> [2015-10-14 14:20:26 +0200]:

> Thanks Nikos,
> 
> Well, actually my training areas are defined as they need to be specific features in my location (rock glaciers). I would like to use i.maxlik to classify the other pixels of my image (other than rock glaciers, alias my training areas). They should be classified as "similar" to my training areas with a certain degree (a certain likelihood). The fact I am only using one band is driven by the fact that only band 4 of Landsat 7 reflectances shows significant difference in value in my training areas than the other unclassified areas. Using twice the same band (band 4) is fine, but I am having difficulties in grouping the same band. Using i.group for instance recognizes that the map is the same and does not add it twice to the group, therefore I cannot use i.maxlik.
> I don't know if producing textures is the way to go in my case, but I will give this a try before rejecting this option. First, however, I need to study this function output.
> Meanwhile, many thanks to both of you (Veronoca and Nikos)! If you have any other useful idea, I will consider them as well.

Umberto,

I am really sorry for not having with me the old project where I did
that, almost.  I recall using the NDVI and as a second input either the
Red or the NIR band.  I think the NIR it was.  And, it worked for me
back then.

I don't have the time to re-create it, or test it properly.  You may
want to fool GRASS by just feeding a copy of the same band, yet with
another name (?).

If you are not bound to use GRASS only, you could check for (open)
alternatives.  There is a comment in
http://gis.stackexchange.com/questions/112544/isodata-classifier-in-qgis
which might be of your interest.

Otherwise, Veronica's suggestion to use an artificial band derived from
your source, is valid as well, me thinks.

Or, alongside the original band, you could use segments filled  with
various stats?  I mean to perform a segmentation (experimenting with the
parameters) and see if you can get segments that serve the distinction
of your wanted objects well.

There is a bullet in i.segment's manual that reads:

"Providing updates to i.maxlik to ensure the segmentation output can be
used as input for the existing classification functionality.".  Don't
know if there is something new regarding this.

So, in any case, the options are many and I am sure there is a good and
effective path to get what you are seeking for.

Nikos



> Umberto
> 
> Il 14/10/15 01:48, Nikos Alexandris  <nik at nikosalexandris.net> ha scritto: 
> > 
> > Umberto:
> > 
> > > 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).
> > 
> > Having already (well defined) training areas is a big step.
> > 
> > 
> > > > Second, I am only interested in using one band for the classification,
> > 
> > Interested or restricted? If more bands are available, and you go the
> > supervised way, why opting for a single-band-based process? Many would
> > rather advise for a segmentation process (aka object-based approach).
> > Of course, to second Veronica, it depends on what the "source"
> > resolution is and what the features of interest are.
> > 
> > 
> > > > which was the reason I could not use "i.maxlik".
> > 
> > Don't hesitate to experiment with the same band twice, I'd say (again).
> > 
> > Nikos
> > 

-- 
Nikos Alexandris | Remote Sensing Scientist, Dr
Themidos 3, 42100, Trikala, Greece
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