HTML prettified

git-svn-id: https://svn.osgeo.org/grass/grass/trunk@48956 15284696-431f-4ddb-bdfa-cd5b030d7da7

imagery/i.cluster/i.cluster.html

@@ -1,16 +1,13 @@
 <h2>DESCRIPTION</h2>
 
-
 <em>i.cluster</em>
 performs the first pass in the GRASS two-pass unsupervised 
 classification of imagery, while the GRASS program <em>
-<a href="i.maxlik.html">i.maxlik</A></em> executes 
+<a href="i.maxlik.html">i.maxlik</a></em> executes 
 the second pass. Both programs must be run to complete the unsupervised 
 classification.
 
-
 <p>
-
 <em>i.cluster</em> is a clustering algorithm that reads
 through the (raster) imagery data and builds pixel clusters
 based on the spectral reflectances of the pixels (see Figure).
@@ -49,7 +46,7 @@ and the row and column sampling intervals.
 The cluster spectral signatures that result are composed of
 cluster means and covariance matrices.  These cluster means
 and covariance matrices are used in the second pass 
-(<em><a href="i.maxlik.html">i.maxlik</A></em>) to
+(<em><a href="i.maxlik.html">i.maxlik</a></em>) to
 classify the image.  The clusters or spectral classes
 result can be related to land cover types on the ground.
 
@@ -62,7 +59,7 @@ that the user wishes to classify.  The <em>subgroup</em> is
 a subset of this group.  The user must create a group and
 subgroup by running the GRASS program
 
-<em><a href="i.group.html">i.group</A></em> 
+<em><a href="i.group.html">i.group</a></em> 
 
 before running <em>i.cluster</em>.  The subgroup should
 contain only the imagery band files that the user wishes to
@@ -72,7 +69,7 @@ collect map layers for classification or analysis. The
 <em>sigfile</em> is the file to contain result signatures
 which can be used as input for
 
-<em><a href="i.maxlik.html">i.maxlik</A></em>. 
+<em><a href="i.maxlik.html">i.maxlik</a></em>. 
 
 The classes value is the initial number of clusters to be
 discriminated; any parameter values left unspecified are
@@ -108,7 +105,7 @@ option, which must contain only imagery band files and more
 than one band file. The user must create a group and a
 subgroup by running the GRASS program 
 
-<em><a href="i.group.html">i.group</A></em> 
+<em><a href="i.group.html">i.group</a></em> 
 
 before
 running <em>i.cluster</em>.
@@ -118,7 +115,7 @@ running <em>i.cluster</em>.
 <dd>The name assigned to output signature file which
 contains signatures of classes and can be used as the input
 file for the GRASS program 
-<em><a href="i.maxlik.html">i.maxlik</A></em> 
+<em><a href="i.maxlik.html">i.maxlik</a></em> 
 for an unsupervised classification.
 
 <dt><b>classes=</b><em>value</em> 
@@ -137,7 +134,7 @@ from a previously run of <em>i.cluster</em> or from a
 supervised classification signature training site section
 (e.g., using the signature file output by
 
-<em><a href="i.class.html">i.class</A></em>). 
+<em><a href="i.class.html">i.class</a></em>). 
 
 The purpose of seed signatures is to optimize the cluster
 decision boundaries (means) for the number of clusters
@@ -157,7 +154,7 @@ predicted to achieve the optimum percent convergence. The
 default value is 30. If the number of iterations reaches
 the maximum designated by the user; the user may want to
 rerun <em>i.cluster</em> with a higher number of iterations
-(see <a href="#reportfile"><em>reportfile</em></A>).
+(see <a href="#reportfile"><em>reportfile</em></a>).
 
 <br>
 
@@ -183,7 +180,7 @@ number of iterations. If the maximum number of iterations
 is reached, it is probable that the desired percent
 convergence was not reached. The number of iterations is
 reported in the cluster statistics in the report file
-(see <a href="#reportfile"><em>reportfile</em></A>).
+(see <a href="#reportfile"><em>reportfile</em></a>).
 
 <br>
 
@@ -201,7 +198,7 @@ minimum class (or cluster) separation is increased, the
 maximum number of iterations should also be increased to
 achieve this separation with a high percentage of
 convergence
-(see <a href="#convergence"><em>convergence</em></A>).
+(see <a href="#convergence"><em>convergence</em></a>).
 
 <br>
 
@@ -218,7 +215,7 @@ calculated.
 
 Default: 17
 
-<A NAME="reportfile"></A>
+<A NAME="reportfile"></a>
 <dt><b>reportfile=</b><em>name</em>
 
 <dd>The reportfile is an optional parameter which contains
@@ -226,7 +223,6 @@ the result, i.e., the statistics for each cluster. Also
 included are the resulting percent convergence for the
 clusters, the number of iterations that was required to
 achieve the convergence, and the separability matrix.
-
 </dl>
 
 
@@ -240,16 +236,16 @@ existed.
 <h2>SEE ALSO</h2>
 
 The GRASS 4 <em>
-<a href="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
-Processing manual</A></em>
+<a href="http://grass.osgeo.org/gdp/imagery/grass4_image_processing.pdf">Image
+Processing manual</a></em>
 
 <p>
 
 <em>
-<a href="i.class.html">i.class</A><br>
-<a href="i.group.html">i.group</A><br>
-<a href="i.gensig.html">i.gensig</A><br>
-<a href="i.maxlik.html">i.maxlik</A>
+<a href="i.class.html">i.class</a>,
+<a href="i.group.html">i.group</a>,
+<a href="i.gensig.html">i.gensig</a>,
+<a href="i.maxlik.html">i.maxlik</a>
 </em>
 
 <h2>AUTHORS</h2>
@@ -259,7 +255,6 @@ U.S.Army Construction Engineering
 Research Laboratory
 
 <br>
-
 Tao Wen, 
 University of Illinois at 
 Urbana-Champaign, 

imagery/i.group/i.group.html

@@ -5,13 +5,13 @@ group by assigning them to user-named subgroups or other groups. This
 enables the user to run analyses on any combination of the raster map layers
 in a group.  The user creates the groups and subgroups and selects the
 raster map layers that are to reside in them. Imagery analysis programs like
-<em><a href="i.points.html">i.points</A></em>, 
-<em><a href="i.rectify.html">i.rectify</A></em>,
-<em><a href="i.ortho.photo.html">i.ortho.photo</A></em> and
+<em><a href="i.points.html">i.points</a></em>, 
+<em><a href="i.rectify.html">i.rectify</a></em>,
+<em><a href="i.ortho.photo.html">i.ortho.photo</a></em> and
 others ask the user for the name of an imagery group whose data are to be
 analyzed. Imagery analysis programs like
-<em><a href="i.cluster.html">i.cluster</A></em> and 
-<em><a href="i.maxlik.html">i.maxlik</A></em> ask the user for the imagery group
+<em><a href="i.cluster.html">i.cluster</a></em> and 
+<em><a href="i.maxlik.html">i.maxlik</a></em> ask the user for the imagery group
 and imagery subgroup whose data are to be analyzed.
 
 
@@ -27,16 +27,16 @@ Subgroup names may not contain more than 12 characters.
 <h2>SEE ALSO</h2>
 
 The GRASS 4 <em>
-<a href="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
-Processing manual</A></em>
+<a href="http://grass.osgeo.org/gdp/imagery/grass4_image_processing.pdf">Image
+Processing manual</a></em>
 
 <p>
 <em>
-<a href="i.cluster.html">i.cluster</A><br>
-<a href="i.maxlik.html">i.maxlik</A><br>
-<a href="i.points.html">i.points</A><br>
-<a href="i.rectify.html">i.rectify</A><br>
-<a href="i.ortho.photo.html">i.ortho.photo</A>
+<a href="i.cluster.html">i.cluster</a>,
+<a href="i.maxlik.html">i.maxlik</a>,
+<a href="i.points.html">i.points</a>,
+<a href="i.rectify.html">i.rectify</a>,
+<a href="i.ortho.photo.html">i.ortho.photo</a>
 </em>
 
 

imagery/i.maxlik/i.maxlik.html

@@ -1,6 +1,5 @@
 <h2>DESCRIPTION</h2>
 
-
 <em>i.maxlik</em> is a maximum-likelihood discriminant
 analysis classifier.  It can be used to perform the second
 step in either an unsupervised or a supervised image
@@ -10,30 +9,28 @@ classification.
 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
+<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="i.class.html">i.class</A></em>. In both cases,
+<a href="i.class.html">i.class</a></em>. In both cases,
 the second step in the image classification procedure is
 performed by <em>i.maxlik</em>.
 
-
 <p>
 In an unsupervised classification, the maximum-likelihood
 classifier uses the cluster means and covariance matrices
-from the <em><a href="i.cluster.html">i.cluster</A></em>
+from the <em><a href="i.cluster.html">i.cluster</a></em>
 signature file to determine to which category (spectral
 class) each cell in the image has the highest probability
 of belonging. In a supervised image classification, the
 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="i.class.html">i.class</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
 <em>i.maxlik</em> is a classified image in which each cell
@@ -41,7 +38,6 @@ 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
@@ -49,7 +45,6 @@ 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> 
@@ -87,25 +82,25 @@ settings; the program will run foreground.
 
 <dt><b>group=</b><em>name</em> 
 
-<dd>The <a href="i.group.html">imagery</A> group 
+<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.
+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>
+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
+<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
@@ -140,12 +135,12 @@ The maximum-likelihood classifier assumes that the spectral
 signatures for each class (category) in each band file
 are normally distributed (i.e., Gaussian in nature).
 Algorithms, such as
-<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>,
+<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>,
 however, can create signatures that are not valid 
 distributed (more likely with 
-<em><a href="i.class.html">i.class</A>).</em>
+<em><a href="i.class.html">i.class</a>).</em>
 If this occurs, 
 <em>i.maxlik</em>
 will reject them and display a warning message.
@@ -161,15 +156,15 @@ existed.
 <h2>SEE ALSO</h2>
 
 The GRASS 4 <em>
-<a href="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
-Processing manual</A></em>
+<a href="http://grass.osgeo.org/gdp/imagery/grass4_image_processing.pdf">Image
+Processing manual</a></em>
 
 <p>
 <em>
-<a href="i.class.html">i.class</A><br>
-<a href="i.cluster.html">i.cluster</A><br>
-<a href="i.gensig.html">i.gensig</A><br>
-<a href="i.group.html">i.group</A>
+<a href="i.class.html">i.class</a>,
+<a href="i.cluster.html">i.cluster</a>,
+<a href="i.gensig.html">i.gensig</a>,
+<a href="i.group.html">i.group</a>
 </em>
 
 <h2>AUTHORS</h2>

imagery/i.rectify/i.rectify.html

@@ -3,9 +3,9 @@
 
 <em>i.rectify</em> uses the control
 points identified in 
-<em><a href="i.points.html">i.points</A></em>
+<em><a href="i.points.html">i.points</a></em>
 or
-<em><a href="i.vpoints.html">i.vpoints</A></em>
+<em><a href="i.vpoints.html">i.vpoints</a></em>
 
 to calculate a transformation matrix based on a first,
 second, or third order polynomial and then converts x,y
@@ -16,9 +16,9 @@ system than before it was rectified).
 
 <p>
 
-<em><a href="i.points.html">i.points</A></em>
+<em><a href="i.points.html">i.points</a></em>
 or
-<em><a href="i.vpoints.html">i.vpoints</A></em>
+<em><a href="i.vpoints.html">i.vpoints</a></em>
 
 must be run before <em>i.rectify</em>, and both programs
 are required to rectify an image. An image must be
@@ -29,7 +29,7 @@ completion of <em>i.rectify</em>, the rectified image is
 deposited in the target standard coordinate LOCATION. This
 LOCATION is selected using
 
-<em><a href="i.target.html">i.target</A></em>.
+<em><a href="i.target.html">i.target</a></em>.
 
 <p>More than one raster map may be rectified at a time. Each cell file
 should be given a unique output file name. The rectified image or
@@ -159,18 +159,18 @@ on the hard drive.
 <h2>SEE ALSO</h2>
 
 The GRASS 4 <em>
-<a href="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
-Processing manual</A></em>
+<a href="http://grass.osgeo.org/gdp/imagery/grass4_image_processing.pdf">Image
+Processing manual</a></em>
 
 <p>
 <em>
-  <a href="m.transform.html">m.transform</A>,
-  <a href="r.proj.html">r.proj</A>,
-  <a href="v.proj.html">v.proj</A>,
-  <a href="i.group.html">i.group</A>,
-  <a href="i.points.html">i.points</A>,
-  <a href="i.vpoints.html">i.vpoints</A>,
-  <a href="i.target.html">i.target</A>
+  <a href="m.transform.html">m.transform</a>,
+  <a href="r.proj.html">r.proj</a>,
+  <a href="v.proj.html">v.proj</a>,
+  <a href="i.group.html">i.group</a>,
+  <a href="i.points.html">i.points</a>,
+  <a href="i.vpoints.html">i.vpoints</a>,
+  <a href="i.target.html">i.target</a>
   <br>
   <a href="wxGUI.GCP_Manager.html">Manage Ground Control Points</a>
 </em>

imagery/i.target/i.target.html

@@ -4,22 +4,22 @@
 group</a> to a GRASS data base location name and mapset.
 
 A location name and mapset are required for the
-<em><a href="i.rectify.html">i.rectify</A></em> imagery module, into which
+<em><a href="i.rectify.html">i.rectify</a></em> imagery module, into which
 to write the rectified map just prior to completion of the program;
 <em>i.target</em> enables the user to specify this location.
 
 <em>i.target</em> must be run before 
-<em><a href="i.points.html">i.points</A></em> and 
-<em><a href="i.rectify.html">i.rectify</A></em>.
+<em><a href="i.points.html">i.points</a></em> and 
+<em><a href="i.rectify.html">i.rectify</a></em>.
 
 <h2>NOTES</h2>
 
 <p>
 The module's first option asks for the name of the
-<a href="i.group.html">imagery group</A> that needs a target.
+<a href="i.group.html">imagery group</a> that needs a target.
 The imagery group must be present in the user's current mapset.
 
-An <a href="i.group.html">imagery group</A> may be targeted to any GRASS
+An <a href="i.group.html">imagery group</a> may be targeted to any GRASS
 location.
 <p>
 If a group name is given without setting options, the currently targeted
@@ -30,16 +30,16 @@ group will be displayed.
 
 The GRASS 4 <em>
 <a href="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
-Processing manual</A></em>
+Processing manual</a></em>
 
 <p>
 <em>
-<a href="i.group.html">i.group</A><br>
-<a href="i.points.html">i.points</A><br>
-<a href="i.vpoints.html">i.vpoints</A><br>
-<a href="i.rectify.html">i.rectify</A>
+<a href="i.group.html">i.group</a>,
+<a href="i.points.html">i.points</a>,
+<a href="i.vpoints.html">i.vpoints</a>,
+<a href="i.rectify.html">i.rectify</a>
 </em><br>
-<em><a href="gm_georect.html">gis.m: GEORECTIFY TOOL</a></em>
+<em><a href="wxGUI.GCP_Manager.html">Manage Ground Control Points</a></em>
 
 
 <h2>AUTHOR</h2>

scripts/r.in.srtm/r.in.srtm.html

@@ -22,7 +22,7 @@ To import TOPEX/SRTM30 PLUS data, use <em>r.in.bin</em>.
 <h2>SEE ALSO</h2>
 
 <em>
-<a href="r.in.bin.html">r.in.bin</A>
+<a href="r.in.bin.html">r.in.bin</a>
 </em>
 <p>
 The <a href="http://www2.jpl.nasa.gov/srtm/">Shuttle Radar Topography Mission</a>
@@ -32,7 +32,7 @@ The <a href="http://pub7.bravenet.com/forum/537683448/">SRTM Web Forum</a>
 
 <h2>REFERENCES</h2>
 
-M. Neteler, 2005. <a href="http://grass.itc.it/newsletter/GRASSNews_vol3.pdf">SRTM and VMAP0 data in OGR and GRASS.</a> <i><a href="http://grass.itc.it/newsletter/">GRASS Newsletter</a></i>, Vol.3, pp. 2-6, June 2005. ISSN 1614-8746.
+M. Neteler, 2005. <a href="http://grass.osgeo.org/newsletter/GRASSNews_vol3.pdf">SRTM and VMAP0 data in OGR and GRASS.</a> <i><a href="http://grass.osgeo.org/newsletter/">GRASS Newsletter</a></i>, Vol.3, pp. 2-6, June 2005. ISSN 1614-8746.
 
 
 <h2>AUTHORS</h2>

vector/v.qcount/v.qcount.html

@@ -10,71 +10,55 @@ point locations from complete spatial randomness.
 <h2>NOTES</h2>
 
 This program may not work properly with lat-long data. It uses 
-<em>hypot()</em>
-in two files: <em>count.c</em> and <em>findquads.c</em>.
+<em>hypot()</em> in two files: <em>count.c</em> and
+<em>findquads.c</em>.
 
 <h2>SEE ALSO</h2>
 
-<em><a href="v.random.html">v.random</A></em> 
+<em><a href="v.random.html">v.random</a></em> 
 
 <p>
-
 <em>Complete Spatial Randomness and Quadrat Methods</em>  - 
 GRASS Tutorial on <em>v.qcount</em>
 (only available as older file s.qcount-tutorial.ps),
 
 <p>
-
 General references include:
 
 <br>
-
 Noel A. C. Cressie.
 <em>Statistics for Spatial Data</em>.
 Wiley Series in Probability and Mathematical Statistics. John Wiley
 &amp; Sons, New York, NY, 1st edition, 1991.
 
 <br>
-
 Brian D. Ripley.
 <em>Spatial Statistics</em>.
 John Wiley \&amp; Sons, New York, NY, 1981.
 
-
 <p>
-
 References to the indices include:
-
 <br>
-
 F. N. David and P. G. Moore.
 Notes on contagious distributions in plant populations.
-<em>Annals of Botany</em>, 
-18:47-53, 1954.
+<em>Annals of Botany</em>, 18:47-53, 1954.
 
 <br>
-
 J. B. Douglas.  Clustering and aggregation.
-<em>Sankhya B</em>, 
-37:398-417, 1975.
+<em>Sankhya B</em>, 37:398-417, 1975.
 
 <br>
-
 R. A. Fisher, H. G. Thornton, and W. A. Mackenzie.
 The accuracy of the plating method of estimating the density of
 bacterial populations.
-<em>Annals of Applied Biology</em>, 
-9:325-359, 1922.
+<em>Annals of Applied Biology</em>, 9:325-359, 1922.
 
 <br>
 
-M. Lloyd.
-Mean crowding.
-<em>Journal of Animal Ecology</em>, 
-36:1-30, 1967.
+M. Lloyd. Mean crowding.
+<em>Journal of Animal Ecology</em>, 36:1-30, 1967.
 
 <br>
-
 M. Morista.
 Measuring the dispersion and analysis of distribution patterns.
 <em>Memoires of the Faculty of Science, Kyushu University, Series E.
@@ -85,21 +69,20 @@ Biology</em>, 2:215-235, 1959.
 Timestamp not working for header part of counts output. (2000-10-28)
 <p>
 Please send all bug fixes and comments to the author
-or the grass development team. <br>
-<a href="http://grass.itc.it"><tt>http://grass.itc.it</tt></a>.
+or the GRASS development team. <br>
+<a href="http://grass.osgeo.org"><tt>http://grass.osgeo.org</tt></a>.
 
-<h2>AUTHOR</h2>
+<h2>AUTHORS</h2>
 
-<a href="http://mccauley-usa.com/">James Darrell McCauley</A>
-<a href="mailto:darrell@mccauley-usa.com">&lt;darrell@mccauley-usa.com&gt;</A>,
+<a href="http://mccauley-usa.com/">James Darrell McCauley</a>
+<a href="mailto:darrell@mccauley-usa.com">&lt;darrell@mccauley-usa.com&gt;</a>,
 <br>when he was at: 
-<a href="http://ABE.www.ecn.purdue.edu/ABE/">Agricultural Engineering</A>
-<a href="http://www.purdue.edu/">Purdue University</A>
+<a href="http://ABE.www.ecn.purdue.edu/ABE/">Agricultural Engineering</a>
+<a href="http://www.purdue.edu/">Purdue University</a>
 
 <p>
 Modified for GRASS 5.0 by Eric G. Miller (2000-10-28)
 <br>
 Modified for GRASS 5.7 by R. Blazek (2004-10-14)
 
-
 <p><i>Last changed: $Date$</i>

vector/v.sample/v.sample.html

@@ -6,7 +6,6 @@ interpolation, bilinear interpolation, or nearest neighbor
 sampling (default).
 
 <p>
-
 This program may be especially useful when sampling for
 cross validation of interpolations whose output is a raster
 map.
@@ -23,12 +22,10 @@ instead.  In these cases, more acurrate results may be obtained
 by using the default nearest neighbor comparisons.
 
 <p>
-
 This program may not work properly with lat-long data when
 the <b>-BC</b> flags are used.
 
 <p>
-
 When interpolation is done (i.e., the <b>-BC</b> flags are
 used), values are assumed to be located at the centroid of
 grid cells.  Therefore, current resolution settings are
@@ -63,22 +60,22 @@ at random places:
 <h2>SEE ALSO</h2>
 
 <em>
-<a href="v.random.html">v.random</A>,
-<a href="g.region.html">g.region</A>
+<a href="v.random.html">v.random</a>,
+<a href="g.region.html">g.region</a>
 </em>
 
 
 <em>Image Sampling Methods</em> - GRASS Tutorial on <em>s.sample</em>
 (available as 
-<a href="http://grass.itc.it/gdp/sites/">s.sample-tutorial.ps.gz</A>) 
+<a href="http://grass.osgeo.org/gdp/sites/">s.sample-tutorial.ps.gz</a>) 
 
 
 <h2>AUTHOR</h2>
 
-<a href="http://mccauley-usa.com/">James Darrell McCauley</A>
+<a href="http://mccauley-usa.com/">James Darrell McCauley</a>
 <br>when he was at: 
-<a href="http://ABE.www.ecn.purdue.edu/ABE/">Agricultural Engineering</A>
-<a href="http://www.purdue.edu/">Purdue University</A>
+<a href="http://ABE.www.ecn.purdue.edu/ABE/">Agricultural Engineering</a>
+<a href="http://www.purdue.edu/">Purdue University</a>
 <p>
 Updated for GRASS 5.0 by Eric G. Miller
 <br>

vector/v.to.points/v.to.points.html

@@ -64,7 +64,7 @@ end of the input line.
 <h2>EXAMPLE</h2>
 
 In this example, the 't_powerlines' vector lines map in the
-<a href="http://grass.itc.it/download/data6.php">Spearfish 6</a>
+<a href="http://grass.osgeo.org/download/data6.php">Spearfish 6</a>
 location is used to create points along the input lines:
 
 <div class="code"><pre>