[GRASS-user] Classifying single landcover

[Daniel Victoria]

Another easy option would be to try an unsupervised classification and
see if the vegetation cover you are interested in falls inside one of
the classes... who knows...

Cheers
Daniel

On Mon, May 23, 2011 at 10:09 AM, Moritz Lennert
<mlennert at club.worldonline.be> wrote:
> On 23/05/11 06:38, Chethan S. wrote:
>>
>> Hi all!
>>
>> For my work I am interested in identifying a single kind of vegetation
>> from LANDSAT Images. If I use signature file with just one signature
>> class(I take many training sites all over the area), the classified
>> image with i.maxlik appears full pink. On the other hand if I randomly
>> pick training sites for one more class(water) and have two classes in
>> the signature file this does not happen. So I am wondering will it not
>> be possible to use a single class's signature sites for supervised
>> classification.
>
> Classification will attribute each pixel to the class with the signature
> closest to the one of the pixel. If you only have one class then this will,
> by definition, always be the closest.
>
> I don't know if there is another way, but if you have a series of threshold
> values for your class in each landsat band, then you could just use
> r.mapcalc to identify those pixels that are within the defined thresholds in
> each band, i.e. something like this:
>
> r.mapcalc myareas = "if((band1>X1 && band1<Y1) && (band2>X2 && band2<Y2) &&
> etc), 1, null())
>
> Moritz
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