Hi, this is my first message to the list. I'm using Grass 6.4.3 under Linuxmint 
16.

I'm trying to make a supervised classification. 

 After digitizing the training areas, I transformed them from vector to raster. 
Then I've done the following:
g.region rast=train_area_2013_03_05_raster@PERMANENT,2013_03_05_toar4@PERMANENT
 then
 i.group group=group subgroup=sub_group 
input=2013_03_05_toar4@PERMANENT,2013_03_05_toar5@PERMANENT,2013_03_05_toar3@PERMANENT
 and 
 i.gensig trainingmap=train_area_2013_03_05_raster@PERMANENT 
group=group@PERMANENT subgroup=sub_group signaturefile=superv_class
 but the resulting signature file, only contains one character: "#".
 The output of i.gensig in the console is the following:
 Finding training classes... 3 classes found Calculating class means... 
Calculating class covariance matrices... Signature 1 not invertible Signature 2 
not invertible Signature 3 not invertible i.gensig complete.  If I try: 
i.maxlik group=group@PERMANENT subgroup=sub_group sigfile=superv_class 
class=results_class
 I obtain the following error message:
 ERROR: Unable to read signature file <superv_class> 
 I've been searching, but I couldn't find the solution. 
 I've tried this: 
http://gis.stackexchange.com/questions/11933/problem-running-i-gensigset-in-grass-any-ideas
 And read this: 
http://gis.stackexchange.com/questions/41418/i-maxlik-cannot-read-i-class-output-signature-file
 But here, there's no solution suggested. As in this case, I also used 
i.cluster to generate an unsupervised signature file and i.maxlik reads this 
perfectly well.
 Here: http://lists.osgeo.org/pipermail/grass-user/2010-April/055821.html
 there's another similar question, but the only answer says: "I suspect that 
either the training areas are suboptimal or are too small."  What does 
suboptimal means? What is an optimal training area? How big should they be?
I have 30 areas, 10 for each class. They aren't too big because I have a small 
site to clasify.
What does "Signature X not invertible" means? Is this the real problem?
 Any idea? Thanks for your help!
 


Lucas.

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