[GRASS-SVN] r35985 -
grass/branches/develbranch_6/vector/v.generalize
svn_grass at osgeo.org
svn_grass at osgeo.org
Fri Feb 20 10:14:53 EST 2009
Author: epatton
Date: 2009-02-20 10:14:53 -0500 (Fri, 20 Feb 2009)
New Revision: 35985
Modified:
grass/branches/develbranch_6/vector/v.generalize/description.html
Log:
Documentation cleanup (part 1): grammar, spelling, etc (merge from trunk, r35984).
Modified: grass/branches/develbranch_6/vector/v.generalize/description.html
===================================================================
--- grass/branches/develbranch_6/vector/v.generalize/description.html 2009-02-20 15:01:27 UTC (rev 35984)
+++ grass/branches/develbranch_6/vector/v.generalize/description.html 2009-02-20 15:14:53 UTC (rev 35985)
@@ -1,249 +1,255 @@
-<H2>DESCRIPTION</H2>
+<h2>DESCRIPTION</h2>
-<EM>v.generalize</EM>
-is module for generalization of GRASS vector maps. This module
-comprises a bunch of algortihms for line simplification, line smoothing,
-network generalization and displacemet. (New methods may be added later)
-Also, this document contains only the descriptions of module and implemented
-methods. For more examples and nice pictures, check
-<EM><A HREF="http://users.ox.ac.uk/~orie1848/tutorial.html">tutorial</A><BR></EM>
+<em>v.generalise</em>
+is a module for the generalization of GRASS vector maps. This module
+consists of algorithms for line simplification, line smoothing,
+network generalization and displacement (new methods may be added later).
+For more examples and nice pictures, see
+<em><a href="http://users.ox.ac.uk/~orie1848/tutorial.html">tutorial</a><br></em>
-<H2>NOTES</H2>
-(Line) simplification is a process of reducing the compexity of vector features.
-It transforms a line into another line which consists of fewer vertices but
-still approximates the original line. The most of the algorithms described below
-selects a subset of points of the original line.
+<h2>NOTES</h2>
+(Line) simplification is a process of reducing the complexity of vector features.
+The module transforms a line into another line consisting of fewer vertices, that
+still approximate the original line. Most of the algorithms described below
+select a subset of points on the original line.
-<P>
-On the other hand, (line) smoothing is a "reverse" process which takes as an
-input a line and produces smoother line which approximates the original line.
-In some cases, this is achieved by inserting new vertices into the line.
-Sometimes, the increase of the number of vertices is dramatical (4000%).
-When this situation occurs, it is always a good idea to simplify the line after
-smoothing.
-</P>
+<p>
+(Line) smoothing is a "reverse" process which takes as input a line and
+produces a smoother approximate of the original.
+In some cases, this is achieved by inserting new vertices into the original line, and can
+total up to 4000% of the number of vertices in the original. In such an instance,
+it is always a good idea to simplify the line after smoothing.
+</p>
-<P>
+<p>
Smoothing and simplification algorithms implemented in this module work line by
-line. i.e simplification/smoothing of one line does not affect the other lines.
-They are treated separately. Also, the first and the last point of each line is
+line, i.e. simplification/smoothing of one line does not affect the other lines;
+they are treated separately. Also, the first and the last point of each line is
never translated and/or deleted.
-</P>
+</p>
-<H2>SIMPLIFICATION</H2>
-<P>
-<EM>v.generalize</EM> contains following line simplification algorithms
-<UL>
-<LI>Douglas-Peucker Algorithm</LI>
-<LI>"Douglas-Peucker Reduction Algorithm"</LI>
-<LI>Lang Algorithm</LI>
-<LI>Vertex Reduction</LI>
-<LI>Reumann-Witkam Algorithm</LI>
-<LI>Remove Small Lines/Areas</LI>
-</UL>
+<h3>SIMPLIFICATION</h3>
+<p>
+<em>v.generalise</em> contains following line simplification algorithms:
+<ul>
+<li>Douglas-Peucker Algorithm</li>
+<li>"Douglas-Peucker Reduction Algorithm"</li>
+<li>Lang Algorithm</li>
+<li>Vertex Reduction</li>
+<li>Reumann-Witkam Algorithm</li>
+<li>Remove Small Lines/Areas</li>
+</ul>
Different algorithms require different parameters, but all the algorithms have
-one parameter in common. It is <B>threshold</B> parameter. In general, the degree
-of simplification increases with the increasing value of <B>threshold</B>.<BR>
+one parameter in common: the <b>threshold</b> parameter. In general, the degree
+of simplification increases with the increasing value of <b>threshold</b>.<br>
-The following happens if <B>r</B> flag is presented.
-If some line is simplified and hence becomes shorter than <B>threshold</B> then it is
-removed. Also, if <B>type</B> contains <B>area</B> and a simplification algorithm is selected,
-the areas of area less than <B>threshold</B> are also removed.
+If the <b>-r</b> flag is passed, simplified lines that become shorter becomes shorter than the
+<b>threshold</b> value are removed. Additionally, if the <b>type</b> parameter contains <b>area</b>
+and a simplification algorithm is selected, then areas less than <b>threshold</b> are also removed.
-<H2>DETAIL DESCRIPTION</H2>
-<UL>
-<LI> <I>Douglas-Peucker</I> - "Quicksort" of line simplification, the most widely used
- algorithm. Input parameters: <B>input</B>, <B>threshold</B>. For more
- information, please check: <A href="http://geometryalgorithms.com/Archive/algorithm_0205/algorithm_0205.htm">http://geometryalgorithms.com/Archive/algorithm_0205/algorithm_0205.htm</A>.</LI>
-<LI> <I>Douglas-Peucker Reduction Algorithm</I> is essentially the same algorithm as the
- algorithm above. The difference is that it takes additional parameter <B>reduction</B>
+<h4>ALGORITHM DESCRIPTIONS</h4>
+<ul>
+<li> <i>Douglas-Peucker</i> - "Quicksort" of line simplification, the most widely used
+ algorithm. Input parameters: <b>input</b>, <b>threshold</b>. For more
+ information, please see: <A href="http://geometryalgorithms.com/Archive/algorithm_0205/algorithm_0205.htm">http://geometryalgorithms.com/Archive/algorithm_0205/algorithm_0205.htm</a>.</li>
+<li> <i>Douglas-Peucker Reduction Algorithm</i> is essentially the same algorithm as the
+ algorithm above, the difference being that it takes additional <b>reduction</b> parameter
which denotes the percentage of the number of points on the new line with respect
- to the number of points on the original line. Input parameters: <B>input</B>,
- <B>threshold</B>, <B>reduction</B>.</LI>
-<LI> <I>Lang</I> - Another standard algorithm. Input parameters: <B>input</B>, <B>threshold</B>, <B>look_ahead</B>.
- For an excellent description, check: <A href="http://www.sli.unimelb.edu.au/gisweb/LGmodule/LGLangVisualisation.htm">http://www.sli.unimelb.edu.au/gisweb/LGmodule/LGLangVisualisation.htm</A>.</LI>
-<LI> <I>Vertex Reduction</I> - Simplest among the algorithms. Input parameters: <B>input</B>, <B>threshold</B>.
- Given line, this algorithm removes the points of this line which are closer to each other than <B>threshold</B>.
- Precisely, if p1 and p2 are two consecutive points and distance between p2 and p1 is less
- than <B>threshold</B>, it removes p2 and repeats the same
- process on the remaining points.</LI>
-<LI> <I>Reuman-Witkam</I> - Input parameters: <B>input</B>, <B>threshold</B>. This algorithm quite
+ to the number of points on the original line. Input parameters: <b>input</b>,
+ <b>threshold</b>, <b>reduction</b>.</li>
+<li> <i>Lang</i> - Another standard algorithm. Input parameters: <b>input</b>, <b>threshold</b>, <b>look_ahead</b>.
+ For an excellent description, see: <A href="http://www.sli.unimelb.edu.au/gisweb/LGmodule/LGLangVisualisation.htm">http://www.sli.unimelb.edu.au/gisweb/LGmodule/LGLangVisualisation.htm</a>.</li>
+<li> <i>Vertex Reduction</i> - Simplest among the algorithms. Input parameters: <b>input</b>, <b>threshold</b>.
+ Given a line, this algorithm removes the points of this line which are closer to each other than <b>threshold</b>.
+ More precisely, if p1 and p2 are two consecutive points, and the distance between p2 and p1 is less
+ than <b>threshold</b>, it removes p2 and repeats the same process on the remaining points.</li>
+<li> <i>Reuman-Witkam</i> - Input parameters: <b>input</b>, <b>threshold</b>. This algorithm quite
reasonably preserves the global characteristics of the lines. For more information
- check <A href="http://www.ifp.uni-stuttgart.de/lehre/vorlesungen/GIS1/Lernmodule/Lg/LG_de_6.html">http://www.ifp.uni-stuttgart.de/lehre/vorlesungen/GIS1/Lernmodule/Lg/LG_de_6.html</A>(german)</LI>
-<LI> <I>Remove Small Lines/Areas</I> - removes the lines (strictly) shorter than threshold and areas of area (strictly)less than threshold.
- Other lines/areas/boundaries are left unchanged. Input parameters: <B>input</B>, <B>threshold</B>
-</UL>
+ see <A href="http://www.ifp.uni-stuttgart.de/lehre/vorlesungen/GIS1/Lernmodule/Lg/LG_de_6.html">http://www.ifp.uni-stuttgart.de/lehre/vorlesungen/GIS1/Lernmodule/Lg/LG_de_6.html</a>(german)</li>
+<li> <i>Remove Small Lines/Areas</i> - removes the lines (strictly) shorter than threshold and areas (strictly) less than threshold.
+ Other lines/areas/boundaries are left unchanged. Input parameters: <b>input</b>, <b>threshold</b>
+</ul>
-<P>
-<I>Douglas-Peucker</I> and <I>Douglas-Peucker Reduction Algorithm</I> use the same method
+<p>
+<i>Douglas-Peucker</i> and <i>Douglas-Peucker Reduction Algorithm</i> use the same method
to simplify the lines. Note that
-<DIV class="code"><PRE>
-v.generalize input=in output=out method=douglas threshold=eps
-</PRE></DIV>
+<div class="code"><pre>
+v.generalise input=in output=out method=douglas threshold=eps
+</pre></div>
is equivalent to
-<DIV class="code"><PRE>
-v.generalize input=in output=out method=douglas_reduction threshold=eps reduction=100
-</PRE></DIV>
+<div class="code"><pre>
+v.generalise input=in output=out method=douglas_reduction threshold=eps reduction=100
+</pre></div>
However, in this case, the first method is faster. Also observe that
-<I>douglas_reduction</I> never outputs more vertices than <I>douglas</I>. And that,
-in general, <I>douglas</I> is more efficient than <I>douglas_reduction</I>.
+<i>douglas_reduction</i> never outputs more vertices than <i>douglas</i>. And that,
+in general, <i>douglas</i> is more efficient than <i>douglas_reduction</i>.
More importantly, the effect of
-<DIV class="code"><PRE>
-v.generalize input=in output=out method=douglas_reduction threshold=0 reduction=X
-</PRE></DIV>
+<div class="code"><pre>
+v.generalise input=in output=out method=douglas_reduction threshold=0 reduction=X
+</pre></div>
+<p>
is that 'out' contains approximately only X% of points of 'in'.
-</P>
+</p>
-<H2>SMOOTHING</H2>
-<P>
-The following smoothing algorithms are implemented in <EM>v.generalize</EM>
-</P>
-<UL>
-<LI><I>Boyle's Forward-Looking Algorithm</I> - The position of each point depends on the
- position of the previous points and the point <B>look_ahead</B> ahead.
- <B>look_ahead</B> consecutive points. Input parameters: <B>input</B>, <B>look_ahead</B>.</LI>
-<LI><I>McMaster's Sliding Averaging Algorithm</I> - Input Parameters: <B>input</B>, <B>slide</B>, <B>look_ahead</B>.
- The new position of each point is the average of the <B>look_ahead</B> points around. Paremeter <B>slide</B>
- is used for linear interpolation between old and new position (see below).</LI>
-<LI><I>McMaster's Distance-Weighting Algorithm</I> - Works by taking the weighted average of <B>look_ahead</B> consecutive points
- where the weight is the reciprocal of the distance from the point to the currently smoothed point. And parameter <B>slide</B> is used
+<h3>SMOOTHING</h3>
+<p>
+The following smoothing algorithms are implemented in <em>v.generalise</em>
+</p>
+<ul>
+<li><i>Boyle's Forward-Looking Algorithm</i> - The position of each point depends on the
+ position of the previous points and the point <b>look_ahead</b> ahead.
+ <b>look_ahead</b> consecutive points. Input parameters: <b>input</b>, <b>look_ahead</b>.</li>
+<li><i>McMaster's Sliding Averaging Algorithm</i> - Input Parameters: <b>input</b>, <b>slide</b>, <b>look_ahead</b>.
+ The new position of each point is the average of the <b>look_ahead</b> points around. Parameter <b>slide</b>
+ is used for linear interpolation between old and new position (see below).</li>
+<li><i>McMaster's Distance-Weighting Algorithm</i> - Works by taking the weighted average of <b>look_ahead</b> consecutive points
+ where the weight is the reciprocal of the distance from the point to the currently smoothed point. And parameter <b>slide</b> is used
for linear interpolation between the original position of the point and newly computed position where value 0 means the original position.
- Input parameters: <B>input</B>, <B>slide</B>, <B>look_ahead</B>.
- </LI>
-<LI><I>Chaiken's Algorithm</I> - "Inscribes" a line touching the original line such that the points on this new line
- are at least <I>threshold</I> apart. Input parameters: <B>input</B>, <B>threshold</B>. This algorithm
- approximates given line very well.</LI>
-<LI> <I>Hermite Interpolation</I> - This algorithm takes the points of the given line as the control
- points of hermite cubic spline and approximates this spline by the points approximatelly <B>threshold</B> apart.
- This method has excellent results for the small values of <B>threshold</B>, but in this case it produces
- a huge number of new points and some simplification is usually needed. Input parameters: <B>input</B>, <B>threshold</B>, <B>angle_thresh</B>.
- <B>Angle_thresh</B> is used for reducing the number of the outputed points. It denotes the minimal
- angle (in degrees) between two consecutive segements of line.</LI>
-<LI> <I>Snakes</I> is the method of minimization of the "energy" of the line. This method preserves the
- general characteristcs of the lines but smooths the "sharp corners" of the line. Input parameters <B>input</B>, <B>alpha</B>, <B>beta</B>.
- This algorithm works very well for small values of <B>alpha</B> and <B>beta</B> (between 0 and 5). These
- parameters affects the "sharpness" and the curvature of the computed line.</LI>
-</UL>
-<P>
-One of the key advantages of <I>Hermite Interpolation</I> is the fact that the computed line
-always passes throught the points of the original line whereas the lines produced by the
+ Input parameters: <b>input</b>, <b>slide</b>, <b>look_ahead</b>.
+ </li>
+<li><i>Chaiken's Algorithm</i> - "Inscribes" a line touching the original line such that the points on this new line
+ are at least <i>threshold</i> apart. Input parameters: <b>input</b>, <b>threshold</b>. This algorithm
+ approximates the given line very well.</li>
+<li> <i>Hermite Interpolation</i> - This algorithm takes the points of the given line as the control
+ points of hermite cubic spline and approximates this spline by the points approximately <b>threshold</b> apart.
+ This method has excellent results for the small values of <b>threshold</b>, but in this case it produces
+ a huge number of new points and some simplification is usually needed. Input parameters: <b>input</b>, <b>threshold</b>, <b>angle_thresh</b>.
+ <b>Angle_thresh</b> is used for reducing the number of the outputed points. It denotes the minimal
+ angle (in degrees) between two consecutive segments of line.</li>
+<li> <i>Snakes</i> is the method of minimisation of the "energy" of the line. This method preserves the
+ general characteristics of the lines but smooths the "sharp corners" of the line. Input parameters <b>input</b>, <b>alpha</b>, <b>beta</b>.
+ This algorithm works very well for small values of <b>alpha</b> and <b>beta</b> (between 0 and 5). These
+ parameters affects the "sharpness" and the curvature of the computed line.</li>
+</ul>
+<p>
+One of the key advantages of <i>Hermite Interpolation</i> is the fact that the computed line
+always passes through the points of the original line, whereas the lines produced by the
remaining algorithms never pass through these points. In some sense, this algorithm outputs
-the line which "circumsrcibes" given line. On the other hand, <I>Chaiken's Algorithm</I> outputs
-the line which "inscribes" given line. Moreover this line always touches/intersects the centre
-of the line segment between two consecutive points. For more iterations, the property above does
-not hold, but the computed lines are very similar to the Bezier Splines. The disadvantage of these
-two algorithm is that they increase the number of points. However, <I>Hermite Interpolation</I> can be used
-as another simplification algorithm. To achieve this, it is necessary to set <I>angle_thresh</I> to higher values (15 or so).
-</P>
-<P>
-One restriction on both McMasters' Algorithms is that <I>look_ahead</I> parameter must be odd. Also
-note that these algorithms have no effect if <I>look_ahead = 1</I>.
-</P>
-<P>
-Note that <I>Boyle's</I>, <I>McMasters'</I> and <I>Snakes</I> algorithm are sometime used in the signal processing to smooth the signals.
-More importantly, these algorithms never change the number of points on the lines. i.e they only
-translate the points, they do not insert any new points.
-</P>
-<P>
-<I>Snakes</I> Algorithm is (asymptotically) the slowest among the algorithms presented above. Also,
-it requires quite a lot of memory. This means, that it is not very efficient
-for maps with the lines consisting of many segments.
-</P>
+a line which "circumscribes" the input line.
+</p>
-<H2>DISPLACEMENT</H2>
-<P>
-The displacement is used when the lines (linear
-features) interact (overlap and/or are close to each other) at the current
-level of detail. In general, displacement methods, as name suggests, move the
-conflicting features apart so that they do not interact and can be distinguished.
-</P>
-<P>
+<p>
+On the other hand, <i>Chaiken's Algorithm</i> outputs a line which "inscribes" a given line.
+The output line always touches/intersects the centre of the input line segment between two
+consecutive points. For more iterations, the property above does not hold, but the computed
+lines are very similar to the Bezier Splines. The disadvantage of the two algorithms given above is that
+they increase the number of points. However, <i>Hermite Interpolation</i> can be used as another
+simplification algorithm. To achieve this, it is necessary to set <i>angle_thresh</i> to higher values (15 or so).
+</p>
+
+<p>
+One restriction on both McMasters' Algorithms is that <i>look_ahead</i> parameter must be odd. Also
+note that these algorithms have no effect if <i>look_ahead = 1</i>.
+</p>
+
+<p>
+Note that <i>Boyle's</i>, <i>McMasters'</i> and <i>Snakes</i> algorithm are sometimes used in the signal processing to smooth the signals.
+More importantly, these algorithms never change the number of points on the lines; they only
+translate the points, and do not insert any new points.
+</p>
+
+<p>
+<i>Snakes</i> Algorithm is (asymptotically) the slowest among the algorithms presented above. Also,
+it requires quite a lot of memory. This means that it is not very efficient for maps with the lines
+consisting of many segments.
+</p>
+
+<h3>DISPLACEMENT</h3>
+<p>
+The displacement is used when the lines overlap and/or are close to each other at the current
+level of detail. In general, displacement methods moves the conflicting features apart so
+that they do not interact and can be distinguished.
+</p>
+
+<p>
This module implements algorithm for displacement of linear features based on
-the <I>Snakes</I> approach. This method has very good results. However, it
+the <i>Snakes</i> approach. This method generally yields very good results; however, it
requires a lot of memory and is not very efficient.
-</P>
-<P>
-Displacement is selected by method=displacement. It uses following parameters:
-</P>
-<UL>
-<LI>
-<B>threshold</B> - specifies critical distance. Two features interact iff they are
-closer than <B>threshold</B> appart.
-</LI>
-<LI>
-<B>alpha</B>, <B>beta</B> - These parameters define the rigidity of lines. For greater
-values of <B>alpha</B>, <B>beta</B> (>=1), the algorithm better preserves the original
-shape of the lines. On the other hand, the lines may not
-be move enough. If the values of <B>alpha</B>, <B>beta</B> are too small (<=0.001)
-then the lines are moved sufficiently, but the geometry and topology of lines can
-be destroyed. Probably, the best way to find the good values of <B>alpha</B>, <B>beta</B>
+</p>
+
+<p>
+Displacement is selected by <b>method=displacement</b>. It uses following parameters:
+</p>
+
+<ul>
+<li>
+<b>threshold</b> - specifies critical distance. Two features interact if they are
+closer than <b>threshold</b> apart.
+</li>
+
+<li>
+<b>alpha</b>, <b>beta</b> - These parameters define the rigidity of lines. For greater
+values of <b>alpha</b>, <b>beta</b> (>=1), the algorithm does a better job at retaining the original
+shape of the lines, possibly at the expense of displacement distance. If the values of <b>alpha</b>,
+<b>beta</b> are too small (<=0.001), then the lines are moved sufficiently, but the geometry and topology of lines can
+be destroyed. Most likely the best way to find the good values of <b>alpha</b>, <b>beta</b>
is by trial and error.
-</LI>
-<LI>
-<B>iterations</B> - denotes the number of iterations the interactions between
-the lines are resolved. Mostly, good values of <B>iterations</B> lies
-between 10 and 100.
-</LI>
-</UL>
-<P>
-The lines affected by the algorithm can be specified by the <B>layer</B>,
-<B>cats</B> and <B>where</B> parameters.
-</P>
+</li>
+
+<li>
+<b>iterations</b> - denotes the number of iterations the interactions between
+the lines are resolved. Good starting points for values of <b>iterations</b> are between 10 and 100.
+</li>
+
+</ul>
+<p>
+The lines affected by the algorithm can be specified by the <b>layer</b>,
+<b>cats</b> and <b>where</b> parameters.
+</p>
<!-- TODO: example(s) -->
-<H2>NETWORK GENERALIZATION</H2>
-<P>
-Is used for selecting "the most important" part of the network. This is based
+<h3>NETWORK GENERALIZATION</h3>
+<p>
+Used for selecting "the most important" part of the network. This is based
on the graph algorithms. Network generalization is applied if method=network.
The algorithm calculates three centrality measures for each line in the
network and only the lines with the values greater than thresholds are selected.
The behaviour of algorithm can be altered by the following parameters:
-</P>
+</p>
-<UL>
-<LI>
-<B>degree_thresh</B> - algorithm selects only the lines which share a point
-with at least <B>degree_thresh</B> different lines.
-</LI>
-<LI>
-<B>closeness_thresh</B> - is always in the range (0, 1]. Only the lines with
-the closeness centrality measure at least <B>closeness_thresh</B> are selcted.
-The lines in the centre of a network have greater values of this measure then
-the lines near the border of a network. This means,
-that this parameters can be used for selecting the centre(s) of a network. Note that
-if closeness_thresh=0 then everything is selected.
-</LI>
-<LI>
-<B>betweeness_thresh</B> - Again, only the lines with betweeness centrality
-measure at least <B>betweeness_thresh</B> are selected. This value is always
+<ul>
+<li>
+<b>degree_thresh</b> - algorithm selects only the lines which share a point
+with at least <b>degree_thresh</b> different lines.
+</li>
+<li>
+<b>closeness_thresh</b> - is always in the range (0, 1]. Only the lines with
+the closeness centrality value at least <b>closeness_thresh</b> apart are selected.
+The lines in the centre of a network have greater values of this measure than
+the lines near the border of a network. This means that this parameter can be used
+for selecting the centre(s) of a network. Note that if closeness_thresh=0 then everything is selected.
+</li>
+<li>
+<b>betweeness_thresh</b> - Again, only the lines with a betweeness centrality
+measure at least <b>betweeness_thresh</b> are selected. This value is always
positive and is larger for large networks. It denotes to what extent a line
is in between the other lines in the network. This value is great for the lines
which lie between other lines and lie on the paths between two parts of a network.
-In the terminology of the road neworks, these are highways, bypasses, main roads/streets....
-</LI>
-</UL>
-<P>
+In the terminology of the road networks, these are highways, bypasses, main roads/streets, etc.
+</li>
+</ul>
+<p>
All three parameters above can be presented at the same time. In that case,
the algorithm selects only the lines which meet each criterion.
-</P>
-<P>
-Also, the outputed network may not be connected if the value of <B>betweeness_thresh</B>
+</p>
+<p>
+Also, the outputed network may not be connected if the value of <b>betweeness_thresh</b>
is too large.
-</P>
+</p>
<!-- TODO: example(s) -->
-<H2>SEE ALSO</H2>
-<EM><A HREF="http://users.ox.ac.uk/~orie1848/tutorial.html">v.generalize Tutorial</A><BR></EM>
-<EM><A HREF="v.clean.html">v.clean</A><BR></EM>
-<EM><A HREF="v.dissolve.html">v.dissolve</A><BR></EM>
-<BR><BR>
+<h2>SEE ALSO</h2>
+<em><a href="http://users.ox.ac.uk/~orie1848/tutorial.html">v.generalise Tutorial</a><br></em>
+<em><a href="v.clean.html">v.clean</a><br></em>
+<em><a href="v.dissolve.html">v.dissolve</a><br></em>
+<br><br>
-<H2>AUTHORS</H2>
+<h2>AUTHORS</h2>
Daniel Bundala, Google Summer of Code 2007, Student
-<BR>
+<br>
Wolf Bergenheim, Mentor
<!-- TODO: references -->
-<P><I>Last changed: $Date$</I>
+<p><i>Last changed: $Date$</i>
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