manual: examples updated

git-svn-id: https://svn.osgeo.org/grass/grass/branches/releasebranch_7_0@63802 15284696-431f-4ddb-bdfa-cd5b030d7da7

display/d.rgb/d.rgb.html

@@ -11,15 +11,19 @@ grey-scale color table.
 
 <em>d.rgb</em> does not attempt to quantize the combined image into a
 fixed number of colors. Nor does it have an option to generate a
-composite layer.
+composite layer (see <em>r.composite</em> for that).
 
 The image and raster maps will not display properly if the graphics
 device does not have a reasonable sampling of the RGB color-space.
 
 <p>
 If color quality of satellite image color composites seems to appear
-poor, run <em><a href="r.colors.html">r.colors</a></em> on the
-selected satellite channels.<p>Example:
+poor, run <em><a href="i.colors.enhance.html">i.colors.enhance</a></em>
+on the selected satellite channels.
+
+<p>
+An alternative is the assignment of grey color tables to each band with
+<em><a href="r.colors.html">r.colors</a></em>:
 
 <div class="code"><pre>
 r.info -r image.1
@@ -33,16 +37,17 @@ r.colors map=image.2 rast=image.1
 r.colors map=image.3 rast=image.1
 </pre></div>
 
-<em>Note: Future GRASS versions may do this for you automatically.</em>
-
 <p>
-To write out the color composite to a R/G/B raster maps, use
+To write out the color composite to a combined R/G/B raster maps, use
 <em><a href="r.composite.html">r.composite</a></em>.
 
 <h2>EXAMPLE</h2>
 
+Visual color composite of a LANDSAT scene (North Carolina sample dataset):
+
 <div class="code"><pre>
-d.rgb red=image.1 green=image.2 blue=image.3
+g.region raster=lsat7_2002_10 -p
+d.rgb blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30
 </pre></div>
 
 <h2>SEE ALSO</h2>

raster/r.coin/r.coin.html

@@ -45,7 +45,6 @@ printed with either 80 or 132 columns.  Finally, the user
 is given the option to rerun the coincidence tabulation
 using a different unit of measurement.
 
-<p>
 <h2>NOTES</h2>
 
 It is <b>not</b> a good idea to run <em>r.coin</em> on a
@@ -56,7 +55,6 @@ reclassify those categories (using <em>r.reclass</em>)
 into a more manageable number prior to running
 <em>r.coin</em> on the reclassed raster map layer.
 
-<p>
 <h2>EXAMPLE</h2>
 
 Below is a sample of tabular output produced by
@@ -169,6 +167,23 @@ to simply rerun the report with different map layers.  In
 order to choose new map layers, it is necessary to rerun
 <em>r.coin.</em>
 
+<!-- North Carolina sample dataset:
+
+Show percentage of each landclass for each town as well as
+the summaries:
+
+<div class="code"><pre>
+g.region raster=landclass96,towns -p
+r.cats landclass96
+r.cats towns
+r.coin -w first=landclass96 second=towns unit=p
+</pre></div>
+
+The result shows that 60% of the current region is located
+in South Raleigh, about half of the area is covered by
+forest and 30% is developed.
+-->
+
 <h2>SEE ALSO</h2>
 
 <em>

raster/r.composite/r.composite.html

@@ -4,7 +4,7 @@ This program combines three raster maps to form a
 composite RGB map. For each input map layer, the corresponding
 component from the map's color table is used (e.g. for
 the red map, the red component is used, and so on). In
-general, the maps should use a gray-scale color table.
+general, the maps should use a grey-scale color table.
 
 <h2>NOTES</h2>
 
@@ -17,11 +17,24 @@ also be significantly slower.
 
 <p>Floyd-Steinberg dithering is optionally used with the <b>-d</b> flag.
 
-<h2>EXAMPLE</h2>
+<h2>EXAMPLES</h2>
+
+<h3>RGB composite of three satellite bands</h3>
+
+Color composite of a LANDSAT scene (North Carolina sample dataset):
+
+<div class="code"><pre>
+g.region raster=lsat7_2002_10
+r.composite blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30 \
+            output=lsat7_2002_rgb
+</pre></div>
+
+<h3>RGB composite with dithering</h3>
 Creating a composite RGB raster using 32 color levels per layer, with dithering:
 
 <div class="code"><pre>
-r.composite -d red=elevation.r green=elevation.g blue=elevation.b output=elev.composite
+r.composite -d red=elevation.r green=elevation.g blue=elevation.b \
+            output=elev.composite
 </pre></div>
 
 <h2>SEE ALSO</h2>
@@ -31,7 +44,7 @@ r.composite -d red=elevation.r green=elevation.g blue=elevation.b output=elev.co
 <a href="d.rgb.html">d.rgb</a>,
 <a href="r.blend.html">r.blend</a>,
 <a href="r.colors.html">r.colors</a>,
-<a href="r.rgb.html">r.rgb</a>,
+<a href="r.rgb.html">r.rgb</a>
 </em>
 <p><em>
 <a href="http://en.wikipedia.org/wiki/Floyd-Steinberg_dithering">Wikipedia Entry: Floyd-Steinberg dithering</a>

raster/r.covar/r.covar.html

@@ -17,18 +17,27 @@ eigen values and eigen vectors. An NxN covariance matrix would result in
 N real eigen values and N eigen vectors (each composed of N real numbers). 
 
 <p>
-The module <em><a href="http://grasswiki.osgeo.org/wiki/AddOns/GRASS_6#m.eigensystem">m.eigensystem</a></em>
+The module <em><a href="http://grasswiki.osgeo.org/wiki/AddOns/GRASS_7/misc#m.eigensystem">m.eigensystem</a></em>
 in <a href="http://grass.osgeo.org/download/addons/">GRASS GIS Addons</a>
 can be compiled and used to generate the eigen values and vectors.
 
 <h2>EXAMPLE</h2>
 
+<!--
+For example (North Carolina sample dataset),
+
+<div class="code"><pre>
+g.region raster=elev_ned_30m -p
+r.covar -r map=elevation,elev_ned_30m,elev_srtm_30m
+</pre></div>
+-->
+
 For example, 
 
-<dl>
-<dd>
-<b>r.covar</b> map=<em>layer.1</em>,<em>layer.2</em>,<em>layer.3</em>
-</dl>
+<div class="code"><pre>
+g.region raster=layer.1 -p
+r.covar -r map=layer.1,layer.2,layer.3
+</pre></div>
 
 would produce a 3x3 matrix (values are example only): 
 
@@ -43,23 +52,20 @@ for the covariance matrix are:
 
 <div class="code"><pre>
 component   eigen value               eigen vector
-    1       1159.745202   &lt; 0.691002    0.720528    0.480511 &gt;
-    2          5.970541   &lt; 0.711939   -0.635820   -0.070394 &gt;
-    3        146.503197   &lt; 0.226584    0.347470   -0.846873 &gt;
+    1       1159.745202   &lt;0.691002  0.720528  0.480511&gt;
+    2          5.970541   &lt;0.711939 -0.635820 -0.070394&gt;
+    3        146.503197   &lt;0.226584  0.347470 -0.846873&gt;
 </pre></div>
 
 The component corresponding to each vector can be produced using 
 <em><a href="r.mapcalc.html">r.mapcalc</a></em>
 as follows: 
 
-<dl>
-<dd>
-<b>r.mapcalc</b> 'pc.1 = 0.691002*layer.1 + 0.720528*layer.2 + 0.480511*layer.3'
-<br>
-<b>r.mapcalc</b> 'pc.2 = 0.711939*layer.1 - 0.635820*layer.2 - 0.070394*layer.3'
-<br>
-<b>r.mapcalc</b> 'pc.3 = 0.226584*layer.1 + 0.347470*layer.2 - 0.846873*layer.3'
-</dl>
+<div class="code"><pre>
+r.mapcalc "pc.1 = 0.691002*layer.1 + 0.720528*layer.2 + 0.480511*layer.3" 
+r.mapcalc "pc.2 = 0.711939*layer.1 - 0.635820*layer.2 - 0.070394*layer.3" 
+r.mapcalc "pc.3 = 0.226584*layer.1 + 0.347470*layer.2 - 0.846873*layer.3"
+</pre></div>
 
 Note that based on the relative sizes of the eigen values, 
 <em>pc.1</em>
@@ -80,10 +86,12 @@ This can be done with <em><a href="r.rescale.html">r.rescale</a></em>.
 
 <h2>SEE ALSO</h2>
 
-<em><a href="i.pca.html">i.pca</a></em>,
-<em><a href="m.eigensystem.html">m.eigensystem</a></em>,
-<em><a href="r.mapcalc.html">r.mapcalc</a></em>,
-<em><a href="r.rescale.html">r.rescale</a></em>
+<em>
+<a href="i.pca.html">i.pca</a>,
+<a href="m.eigensystem.html">m.eigensystem</a> (Addon),
+<a href="r.mapcalc.html">r.mapcalc</a>,
+<a href="r.rescale.html">r.rescale</a>
+</em>
 
 <h2>AUTHOR</h2>