[GRASS-user] Classifying single landcover

[Moritz Lennert]

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