[GRASS-user] why is landcover class being lost on classification

[Samantha Goodchild-Brown]

Can anybody tell me why the classification I so carefully preserve on 
v.to.rast from my training data does not reflect on my classification?

When I query my vector training data I get:
v.what --v -a map=traintest210912a at 3420 
east_north=-80606.881455,-3785043.808541 distance=388.789822

East: -80606.881455

North: -3785043.808541

Map: traintest210912a

Mapset: 3420

Type: Area

Sq Meters: 6133078.387

Hectares: 613.308

Acres: 1515.517

Sq Miles: 2.3680

Layer: 1

Category: 1

Driver: dbf

Database: /home/tms/LC_NGIqxx/LO21/3420/dbf/

Table: traintest210912a

Key column: cat

cat : 1

cat_ : 12

label : shrubs and bushes

rgb : 38: 181: 113

Building spatial index...

(Thu Sep 27 14:29:00 2012) Command finished (0 sec)


When I convert this to raster ensuring 'cat_' remains the key column and 
I query the resulting raster I get:

r.what --v -f input=trainteset1_rast at 3420 
east_north=-80568.002473,-3785121.566505

-80568.002473|-3785121.566505||12|

(Thu Sep 27 14:30:58 2012) Command finished (0 sec)


And when I query the classification after running i.gensig and i.maxlik, 
I get:

r.what --v -f input=sclasstest1 at 3420 
east_north=-80412.486544,-3783994.076020

-80412.486544|-3783994.076020||1|

(Thu Sep 27 14:31:57 2012) Command finished (0 sec)


Which means I am now forced to repeat myself and run recode or reclass, 
after going to the hassle of setting  the classification codes for a 
supervised classificaton in the begining.
It would make sense to me if I had run i.class (as per the older 
documentation I have found that doesn't include i.gensig), but not with 
a training map.

Is there maybe a background setting I haven't found yet that I need to 
set? Or is this how it is supposed to run? In which case, is there a 
technical reason for this that I am missing?

Thank you
Sam
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