Hi GRASS USERS,
I wanted to do supervised classification.For that I had several training data sets-namely builtup, agriculture,waste,water etc in vector form.I digitized those training data through v.digit and labelled them as lines and gave them category values.Then I converted them to raster form through v.to.rast command.Finally I executed the querry after running the command r.mapcalc as
<output_map>=if((builtup_map==1) || (agriculture_map==2).....).The combined raster map was obtained as <output_map> having all the categories I named during digitizing (category 1,category 2,category 3..). The problem is that the pixels in the raster map consists of only one color representing all the categories instead of different colors for different categories which can be seen when one displays the raster images separatly for each category in a separate window.(eg. blue for water, yellow for agriculture, red for builtup...).The resultant file after combining all the training data sets was put as a signature file for the command i.gensig.The resulting output was used as a input for i.maxlik.What I get in last is a raster image of only one colour and other categories are not seen.Yet they can be seen while running d.legend. My problem is how to use available training data sets in GRASS through i.gensig or i.class for using in i.maxlik for performing supervised classification.
Please help
regards,
uttam.
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