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

[Umberto Filippo Minora]

Thanks again Moritz.
Of course I have other strategies to map permafrost, not only this, but I'd rather use them in a second phase. For instance, I have cumulative global radiation data during summer derived with r.sun function and summed up. I used these data to perform a parallel classification by setting an upper value of cumulative value to my rock glaciers (75th percentile in my dataset), and keep only thise pixels to be classified which fall below this threshold. then I will perform the band 4 (let's call it "spectral classification"), AND I will overlap the two (and surely the info from the DEM), into a final classification according to certain criteria which I have in my mind.
@Nikos. Thanks again for the suggestion. I already tried the PCA but it gave me no interesting results in view of my classificaiton. I will try to fool the i.maxlik by creating a group with band 4 and a copy of it with modified name and see what will happen.
Again, many thanks to all the precious sugegstions, I didn' expect such partecipation and I am considering all your precious hints!

Il 14/10/15 17:59, Moritz Lennert  <mlennert a club.worldonline.be> ha scritto: 
> 
> On 14/10/15 17:40, Nikos Alexandris wrote:
> >
> >Moritz Lennert:
> >
> >>If you only work with one band, you could use your training areas to
> >>define the mean value and standard deviation in band 4 that corresponds
> >>to your class of interest and then just use r.recode to classify your
> >>image with something like this:
> >>
> >>mean-stddev:mean+stddev:1
> >>*:0
> >
> >Interesting. But that would depend a lot of how big the study extent
> >is, how many the training areas are, how they are spread, the illumination
> >geometry of the input acquisition, and more I guess.
> 
> This problem is present whatever your technique. But technically, unless I'm completely mistaken, what I propose is a real maximum likelihood classification. i.maxlik could not do anything else with only one band.
> 
> Using just the info of one band to identify such features sounds quite hazardous to me, though. More auxiliary info would be better. Segmenting the image and then filling the polygon attribute table with other info (which could include infos derived from a DEM or other layers) might be the best way to go.
> 
> Moritz
> 
> 
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