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<h2>NAME</h2>
<em><b>i.gensig</b></em> - Generates statistics for i.maxlik from raster map.
<h2>KEYWORDS</h2>
imagery, classification, supervised, MLC
<h2>SYNOPSIS</h2>
<b>i.gensig</b><br>
<b>i.gensig help</b><br>
<b>i.gensig</b> <b>trainingmap</b>=<em>name</em> <b>group</b>=<em>name</em> <b>subgroup</b>=<em>name</em> <b>signaturefile</b>=<em>string</em> [--<b>verbose</b>] [--<b>quiet</b>]
<h3>Parameters:</h3>
<DL>
<DT><b>trainingmap</b>=<em>name</em></DT>
<DD>Ground truth training map</DD>
<DT><b>group</b>=<em>name</em></DT>
<DD>Name of input imagery group</DD>
<DT><b>subgroup</b>=<em>name</em></DT>
<DD>Name of input imagery subgroup</DD>
<DT><b>signaturefile</b>=<em>string</em></DT>
<DD>Name for output file containing result signatures</DD>
</DL>
<h2>DESCRIPTION</h2>
<em>i.gensig</em>
is a non-interactive method for generating input into
<em><a href="i.maxlik.html">i.maxlik</a></em>.
It can be used as the first pass in the GRASS two-pass
classification process (instead of
<em><a href="i.cluster.html">i.cluster</a></em>
or
<em><a href="i.class.html">i.class</a></em>).
It reads a raster map layer, called the training map, which
has some of the pixels or regions already classified.
<em>i.gensig</em> will then extract spectral signatures
from an image based on the classification of the pixels in
the training map and make these signatures available to
<em><a href="i.maxlik.html">i.maxlik</a></em>.
<p>
The user would then execute the GRASS program
<em><a href="i.maxlik.html">i.maxlik</a></em>
to actually create the final classified map.
<h2>OPTIONS</h2>
<h3>Parameters</h3>
<dl>
<dt><b>trainingmap=</b><em>name</em>
<dd>ground truth training map
<p>
This map must be prepared by the user in advance. Programs like
<em><a href="v.digit.html">v.digit</a></em> or <em>
<a href="r.digit.html">r.digit</a></em> can be
used to define representative
areas of the classes the user defines to be in the image.
Of course other methods could be devised by the user for creating
this training map - <em>i.gensig</em> makes no assumption about the origin
of this map layer. It simply creates signatures for the classes defined
in the training map for the image to be classified (the image is
specified in other options - see below).
<dt><b>group=</b><em>name</em>
<dd>imagery group
<p>
This is the name of the group that contains the band files
which comprise the image to be analyzed. The <em>
<a href="i.group.html">i.group</a> </em> command is
used to construct groups of raster layers which comprise an
image.
<p>
<A NAME="subgroup"><dt><b>subgroup=</b><em>name</em></a>
<dd>subgroup containing image files
<p>
This names the subgroup within the group that selects a
subset of the bands to be analyzed. The <em>
<a href="i.group.html">i.group</a> </em> command is
also used to prepare this subgroup. The subgroup mechanism
allows the user to select a subset of all the band files
that form an image.
<dt><b>signaturefile=</b><em>name</em>
<dd>resultant signature file
<p>
This is the resultant signature file (containing the means
and covariance matrices) for each class in the training map
that is associated with the band files in the subgroup
select (see <a href="#subgroup">above</a>).
</dl>
<h2>INTERACTIVE MODE</h2>
If none of the arguments are specified on the command line,
<em>i.gensig</em>
will interactively prompt for the names of these maps and files.
<p>
It should be noted that interactive mode here only means
interactive prompting for maps and files.
It does not mean visualization of the signatures that
result from the process.
<h2>NOTES</h2>
The structure of the SIG files generated by <em>i.gensig</em> is
as follows (ASCII file, used internally by <em>i.maxlik</em>):
<br>
<i>Note: the line numbers are not present in the file but have been
added here for explanation only</i>:
<p>
SIG file "lsat7_2000_gensig":
<div class="code"><pre>
1 #
2 #water
3 4186
4 67.9508 48.7346 37.8915 15.3129 13.8473 12.0855
5 1.74334
6 0.439504 2.07267
7 0.662523 1.63501 4.21189
8 0.530339 2.40757 5.52857 22.433
9 0.561184 2.30762 5.18846 20.5364 20.4926
10 0.393218 1.2184 2.63628 9.61528 9.36025 5.85314
</pre></div>
<ul>
<li> Line 2: text label
<li> Line 3: number of points in class
<li> Line 4: mean values per band of the class
<li> Line 5-10: (semi)-matrix of band-band covariance
</ul>
<h2>SEE ALSO</h2>
<em><a href="i.group.html">i.group</a></em>
for creating groups and subgroups.
<p>
<em><a href="v.digit.html">v.digit</a></em>
and
<em><a href="r.digit.html">r.digit</a></em>
for interactively creating the training map.
<p>
<em><a href="i.cluster.html">i.cluster</a></em>
for unsupervised clustering as an alternative to
<em>i.gensig</em> to create signatures.
<p>
<em><a href="i.class.html">i.class</a></em>
for a graphic/interactive as an alternative to
<em>i.gensig</em> to create signatures.
<h2>AUTHOR</h2>
Michael Shapiro,
U.S.Army Construction Engineering Research Laboratory
<p><i>Last changed: $Date: 2013-06-09 14:37:33 +0200 (Sun, 09 Jun 2013) $</i>
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