I have three maps which are 1) shortwave infrared reflectances derived
from Landsat ETM+ (Data Type: FCELL); 2) cumulative solar radiation
derived using "r.sun" from GRASS (Data Type: FCELL); 3) elevation map
(DEM, Data Type: CELL).
I am trying to perform a supervised maximum likelihood classification
over these bands.
So, first I grouped them using "i.group".
Then I imported a shp with rock glacier areas, created a new column in
its attribute table called "IDmaxlik" and assigned a value of "1" (int)
to it.
Then I converted the shp to raster with this command:
v.to.rast in=rg_visible out=rg_visible use=attr
attribute_column=IDmaxlik
and I used "i.gensig" to generate the signature file.
i.gensig trainingmap=rg_visible group=perma_max subgroup=perma_max
signaturefile=rg_sig
Finally, I run "i.maxlik":
i.maxlik group=perma_max subgroup=perma_max signaturefile=rg_sig
output=classification01 reject=classification01_reject
Each pixel of the output map ("classification01") is 1, as if the
everything was classified as "rock glacier". Moreover, the reject map
("classification01_reject"), has higher values (closer to 16, or 100%)
over the same rock glaciers used as the region of interest than elsewhere.
Might be the problem related to the fact that "i.gensig" expected a clip
of the RGB raster on the ROIs, rather than a mask?
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