[GRASS-SVN] r59813 - grass/trunk/imagery/i.maxlik

[svn_grass at osgeo.org]

Author: martinl
Date: 2014-04-19 11:47:36 -0700 (Sat, 19 Apr 2014)
New Revision: 59813

Modified:
   grass/trunk/imagery/i.maxlik/i.maxlik.html
Log:
i.maxlik: major manual clean-up


Modified: grass/trunk/imagery/i.maxlik/i.maxlik.html
===================================================================
--- grass/trunk/imagery/i.maxlik/i.maxlik.html	2014-04-19 18:38:08 UTC (rev 59812)
+++ grass/trunk/imagery/i.maxlik/i.maxlik.html	2014-04-19 18:47:36 UTC (rev 59813)
@@ -9,11 +9,10 @@
 Either image classification methods are performed in two
 steps.  The first step in an unsupervised image
 classification is performed by
-<em><a href="i.cluster.html">i.cluster</a></em>; the
-first step in a supervised classification is executed by
-the GRASS program <em>
-<a href="g.gui.iclass.html">g.gui.iclass</a>. In both cases,
-the second step in the image classification procedure is
+<em><a href="i.cluster.html">i.cluster</a></em>; the first step in a
+supervised classification is executed by the GRASS
+program <em><a href="g.gui.iclass.html">g.gui.iclass</a></em>. In both
+cases, the second step in the image classification procedure is
 performed by <em>i.maxlik</em>.
 
 <p>
@@ -26,97 +25,18 @@
 maximum-likelihood classifier uses the region means and
 covariance matrices from the spectral signature file
 generated by <em>
-<a href="i.class.html">i.class</a></em>, based on regions
+<a href="g.gui.iclass.html">g.gui.iclass</a></em>, based on regions
 (groups of image pixels) chosen by the user, to determine
 to which category each cell in the image has the highest
 probability of belonging.
 
 <p>
-In either case, the raster map layer output by
+In either case, the raster map output by
 <em>i.maxlik</em> is a classified image in which each cell
 has been assigned to a spectral class (i.e., a category).
 The spectral classes (categories) can be related to
 specific land cover types on the ground.
 
-<p>
-The program will run non-interactively if the user
-specifies the names of raster map layers, i.e., group and
-subgroup names, seed signature file name, result
-classification file name, and any combination of
-non-required options in the command line, using the form
-
-<dl>
-<dd>
-<b>i.maxlik</b>[<b>-q</b>] <b>group=</b><em>name</em> 
-<b>subgroup=</b><em>name</em>
-<b>sigfile=</b><em>name</em> <b>class=</b><em>name</em> 
-[<b>reject=</b><em>name</em>]
-</dl>
-
-where each flag and options have the meanings stated below.
-
-<p>
-Alternatively, the user can simply type <em>i.maxlik</em>
-in the command line without program arguments. In this case
-the user will be prompted for the program parameter
-settings; the program will run foreground.
-
-<h2>OPTIONS</h2>
-
-<h3>Parameters:</h3>
-
-<dl>
-
-<dt><b>group=</b><em>name</em> 
-
-<dd>The <a href="i.group.html">imagery</a> group 
-contains the subgroup to be classified.
-
-<dt><b>subgroup=</b><em>name</em> 
-
-<dd>The subgroup contains image files, which were used to create 
-the signature file
-in the program <em><a href="i.cluster.html">i.cluster</a></em>, 
-<em><a href="i.class.html">i.class</a></em>, or 
-<em><a href="i.gensig.html">i.gensig</a></em> to be classified.
-
-<dt><b>sigfile=</b><em>name</em> 
-
-<dd>The name of the signatures to be used for the
-classification. The signature file contains the cluster and
-covariance matrices that were calculated by the GRASS
-program <em><a href="i.cluster.html">i.cluster</a></em>
-(or the region means and covariance matrices generated by
-<em><a href="i.class.html">i.class</a></em>, if the
-user runs a supervised classification). These spectral
-signatures are what determine the categories (classes) to
-which image pixels will be assigned during the
-classification process.
-
-<dt><b>class=</b><em>name</em> 
-
-<dd>The name of a raster map holds the classification
-results. This new raster map layer will contain categories
-that can be related to land cover categories on the
-ground.
-
-<dt><b>reject=</b><em>name</em> 
-
-<dd>The optional name of a raster map holds the reject
-threshold results. This is the result of a chi square test
-on each discriminant result at various threshold levels of
-confidence to determine at what confidence level each cell
-classified (categorized). It is the reject threshold map
-layer, and contains the index to one calculated confidence level for
-each classified cell in the classified image. 16 confidence intervals 
-are predefined, and the reject map is to be interpreted as 1 = keep and 
-16 = reject. One of the possible uses for this map layer is as a mask, 
-to identify cells in the classified image that have a low
-probability (high reject index) of being assigned to the correct 
-class.
-</dl>
-
-
 <h2>NOTES</h2>
 
 The maximum-likelihood classifier assumes that the spectral 
@@ -134,17 +54,33 @@
 will reject them and display a warning message.
 
 <p>
-This program runs interactively if the user types
-<em>i.maxlik</em> only. If the user types <em>i.maxlik</em>
-along with all required options, it will overwrite the
-classified raster map without prompting if this map
-existed.
+The signature file (<b>signaturefile</b>) contains the cluster and
+covariance matrices that were calculated by the GRASS
+program <em><a href="i.cluster.html">i.cluster</a></em> (or the region
+means and covariance matrices generated by
+<em><a href="g.gui.iclass.html">g.gui.iclass</a></em>, if the user
+runs a supervised classification). These spectral signatures are what
+determine the categories (classes) to which image pixels will be
+assigned during the classification process.
 
+<p>
+The optional name of a <b>reject</b> raster map holds the reject
+threshold results. This is the result of a chi square test on each
+discriminant result at various threshold levels of confidence to
+determine at what confidence level each cell classified
+(categorized). It is the reject threshold map layer, and contains the
+index to one calculated confidence level for each classified cell in
+the classified image. 16 confidence intervals are predefined, and the
+reject map is to be interpreted as 1 = keep and 16 = reject. One of
+the possible uses for this map layer is as a mask, to identify cells
+in the classified image that have a low probability (high reject
+index) of being assigned to the correct class.
+
 <h2>EXAMPLE</h2>
 
 Completion of the unsupervised classification of
 a LANDSAT subscene (VIZ, NIR, MIR channels) in North Carolina
-(see <em>i.cluster</em> manual page for the first part):
+(see <em><a href="i.cluster.html">i.cluster</a></em> manual page for the first part):
 
 <div class="code"><pre>
 i.maxlik group=my_lsat7_2002 subgroup=my_lsat7_2002 sigfile=sig_clust_lsat2002 \