[GRASS-SVN] r72242 - grass-addons/grass7/raster/r.pi
svn_grass at osgeo.org
svn_grass at osgeo.org
Thu Feb 15 08:53:18 PST 2018
Author: neteler
Date: 2018-02-15 08:53:17 -0800 (Thu, 15 Feb 2018)
New Revision: 72242
Added:
grass-addons/grass7/raster/r.pi/r.pi.html
Removed:
grass-addons/grass7/raster/r.pi/description.html
Log:
r.pi addon manual: use standard name
Deleted: grass-addons/grass7/raster/r.pi/description.html
===================================================================
--- grass-addons/grass7/raster/r.pi/description.html 2018-02-14 20:10:15 UTC (rev 72241)
+++ grass-addons/grass7/raster/r.pi/description.html 2018-02-15 16:53:17 UTC (rev 72242)
@@ -1,207 +0,0 @@
-<h2>DESCRIPTION</h2>
-
-<em>r.pi</em> (raster patch index) provides various functions to analyse
-spatial attributes of a landscape. It has a focus on patch-based indices
-but delivers class-based indices as well. <em>r.le</em> and its successor
-<em>r.li</em> provide landscape indices.
-
-<p>
-A list with a short description of the <em>r.pi</em> modules can be found
-below. More in depth description of a certain module (commands, flags,
-options) can be found in the respective folder (like
-<em><a href="r.pi.graph.html">r.pi.graph</a></em>). The functions/algorithms
-of the modules are not yet very extensive but will be expanded in the
-future. Please submit any bug/feature you might encounter to improve the
-functionality.
-<p>
-The program will interactively query the user for input, output and
-options (GUI). However the module can be also run from the terminal
-prompt (CLI) and might be implemented in e.g. a bash-script.
-<p>
-It is highly recommended to read the help pages or e.g the overview
-documents of
-<a href="http://www.umass.edu/landeco/research/fragstats/documents/fragstats_documents.html">Fragstats</a>
-to get a better impression of problems, possibilities and caveats.
-
-
-<h2>OVERVIEW</h2>
-
-<li><em>r.pi.rectangle</em> - Performs statistical analysis on values of patches from the given raster map.
-<li><em>r.pi.energy</em> - Individual-based dispersal model for connectivity analysis - energy based.
-<li><em>r.pi.energy.pr</em> - Individual-based dispersal model for connectivity analysis (energy based) using iterative patch removal.
-<li><em>r.pi.fragment.dist</em> - Calculates correlation of two raster maps by calculating correlation function of two corresponding rectangular areas for each raster point and writing the result into a new raster map.
-<li><em>r.pi.enn</em> - Determines patches of given value and performs a nearest-neighbor analysis.
-<li><em>r.pi.index</em> - Computation of fragmentation indices.
-<li><em>r.pi.enn.pr</em> - Patch relevance for Euclidean Nearest Neighbor patches.
-<li><em>r.pi.neigh</em> - Neighbourhood analysis - value of patches within a defined range.
-<li><em>r.pi.enn</em> - Analysis of n-th Euclidean Nearest Neighbor distance.
-<li><em>r.pi.nlm</em> - Creates a random generated map with values 0 or 1by given landcover and fragment count.
-<li><em>r.pi.nlm.circ</em> - Creates a random landscape with defined attributes.
-<li><em>r.pi.nlm.stats</em> - Neutral Landscape Generator - index statistics
-<li><em>r.pi.corearea</em> - Variable edge effects and core area analysis
-<li><em>r.pi.corr.mw</em> - Moving window correlation analysis.
-<li><em>r.pi.csr.mw</em> - Complete Spatial Randomness analysis on moving window.
-<li><em>r.pi.export</em> - Export of patch based information.
-<li><em>r.pi.graph</em> - Graph Theory for connectivity analysis.
-<li><em>r.pi.graph.pr</em> - Graph Theory - iterative removal (patch relevance analysis).
-<li><em>r.pi.graph.red</em> - Graph Theory - decreasing distance threshold option.
-<li><em>r.pi.grow</em> - Size and suitability based region growing.
-<li><em>r.pi.import</em> - Import and generation of patch raster data
-<li><em>r.pi.index</em> - Basic patch based indices
-<li><em>r.pi.lm</em> - Linear regression analysis for patches.
-<li><em>r.pi.prob.mw</em> - Probability analysis of 2 random points being in the same patch.
-<li><em>r.pi.rectangle</em> - Generates a rectangle based on a corner coordinate.
-<li><em>r.pi.searchtime</em> - Individual-based dispersal model for connectivity analysis (time-based)
-<li><em>r.pi.searchtime.pr</em> - Individual-based dispersal model for connectivity analysis (time-based) using iterative removal of patches
-<li><em>r.pi.searchtime.mw</em> - Individual-based dispersal model for connectivity analysis (time-based) using moving window
-
-
-<h3>General and Connectivity Indices</h3>
-
-<ul>
-<li><b><a href="r.pi.index.html">r.pi.index</a></b>: Calculations of basic indices (area, SHAPE etc.) </li>
-<li><b><a href="r.pi.enn.html">r.pi.enn</a></b>: Area, SHAPE and distance to n-th Euclidean Nearest Neighbor</li>
-<li><b><a href="r.pi.fnn.html">r.pi.fnn</a></b>: Area, SHAPE and distance to n-th Functional Nearest Neighbor</li>
-<li><b><a href="r.pi.odc.html">r.pi.odc</a></b>: Area and distance to omnidirectional n-th Nearest Neighbors</li>
-<li><b><a href="r.pi.neigh.html">r.pi.neigh</a></b>: Extraction of values of patches in defined buffer region</li>
-<li><b><a href="r.pi.prox.html">r.pi.prox</a></b>: Calculation of Proximity and Modified Proximity Index for patches in buffer region</li>
-<li><b><a href="r.pi.graph.html">r.pi.graph</a></b>: Various connectivity indices within the Graph Theory </li>
-</ul>
-
-
-<h3>Individual-based dispersal models</h3>
-<ul>
-<li><b><a href="r.pi.searchtime.html">r.pi.searchtime</a></b>:Searchtime and Immigration rate</li>
-<li><b><a href="r.pi.energy.html">r.pi.energy</a></b>: Immigration, Migration and successfull emigration rate</li>
-<li><b><a href="r.pi.searchtime.mw.html">r.pi.searchtime.mw</a></b>:Related to <em>r.pi.searchtime</em> but using a Moving Windows approach</li>
-</ul>
-
-<h3>Patch-Relevance</h3>
-<ul>
-<li><b><a href="r.pi.enn.pr.html">r.pi.enn.pr</a></b>:Relevance of patches for maintenance of distance to first Nearest Neighbor</li>
-<li><b><a href="r.pi.searchtime.pr.html">r.pi.searchtime.pr</a></b>:Relevance of patches for maintenance of searchtime</li>
-<li><b><a href="r.pi.energy.pr.html">r.pi.energy.pr</a></b>:Relevance of patches for maintenance of immigration rate</li>
-<li><b><a href="r.pi.graph.red.html">r.pi.graph.red</a></b>:Relevance of patches ....</li>
-<li><b><a href="r.pi.graph.dec.html">r.pi.graph.dec</a></b>:Relevance of patches ....</li>
-</ul>
-
-<h3>Neutral Landscape Model</h3>
-<ul>
-<li><b><a href="r.pi.nlm.html">r.pi.nlm</a></b>: Generation of a neutral landscape (fractal)</li>
-<li><b><a href="r.pi.nlm.stats.html">r.pi.nlm.stats</a></b>:Statistical analysis of landscapes based on permutation of neutral landscapes</li>
-<li><b><a href="r.pi.nlm.circ.html">r.pi.nlm.circ</a>c</b>:Generation of a neutral landscape (circular)</li>
-</ul>
-
-<h3>Various modules</h3>
-<ul>
-<li><b><a href="r.pi.corearea.html">r.pi.corearea</a></b>:Calculation of core area based on costmatrix</li>
-<li><b><a href="r.pi.prob.mw.html">r.pi.prob.mw</a></b>:Probability of two random points being in the same patch</li>
-<li><b><a href="r.pi.rectangle.html">r.pi.rectangle</a></b>: Generation of rectangles based on coordinate points</li>
-<li><b><a href="r.pi.import.html">r.pi.import</a></b>:Import of values to corresponding patches</li>
-<li><b><a href="r.pi.export.html">r.pi.export</a></b>:Export of values from patches</li>
-<li><b><a href="r.pi.lm.html">r.pi.lm</a></b>:Residuals of a Linear Regression between 2 rasters are provided as raster</li>
-<li><b><a href="r.pi.corr.mw.html">r.pi.corr.mw</a></b>:Moving window correlation between two raster maps</li>
-</ul>
-
-<h2>EXAMPLES</h2>
-
-<h4>Calculation of the SHAPE-Index</h4>
-
-Input can be generated by <em>r.pi.nlm</em>, for example:
-
-<div class="code"><pre>
-# generate random landscape with 50% cover
-r.pi.nlm output=NLM_in landcover=50 sharpness=0.5
-
-# use the class 1 of the above generated landscape for computation of SHAPE-Index
-r.pi.index input=NLM_in keyval=1 output=NLM_in.shape method=shape
-</pre></div>
-
-
-<h4>Calculation of the distance to the first and 10th Nearest Neighbor</h4>
-
-Input generated by <em>r.pi.nlm</em>, for example:
-
-<div class="code"><pre>
-# generate random landscape with 50% cover
-r.pi.nlm output=NLM_in landcover=50 sharpness=0.5
-
-# first NN
-r.pi.index input=NLM_in keyval=1 output=NLM_in.enn1 method=ENN
-
-# 10th NN
-r.pi.enn input=NLM_in output=NLM_in.enn10 method=distance number=10
-
-# 1-10th NN
-r.pi.enn input=NLM_in output=NLM_in.enn10 method=distance number=1-10
-</pre></div>
-
-
-<h2>NOTE</h2>
-
-The maximum number of patches that can be queried at one time depend on
-the module and might also be influenced by the resolution.
-
-<h2>SEE ALSO</h2>
-
-<em>
-<a href="r.pi.corr.mw.html">r.pi.corr.mw</a>,
-<a href="r.pi.energy.html">r.pi.energy</a>,
-<a href="r.pi.energy.pr.html">r.energy.pr</a>,
-<a href="r.pi.enn.html">r.pi.enn</a>,
-<a href="r.pi.enn.pr.html">r.pi.enn.pr</a>,
-<a href="r.pi.neigh.html">r.pi.neigh</a>,
-<a href="r.pi.fnn.html">r.pi.fnn</a>,
-<a href="r.pi.nlm.circ.html">r.pi.nlm.circ</a>,
-<a href="r.pi.nlm.html">r.pi.nlm</a>,
-<a href="r.pi.nlm.stats.html">r.nlm.stats</a>,
-<a href="r.pi.corearea.html">r.pi.corearea</a>,
-<a href="r.pi.csr.mw.html">r.pi.csr.mw</a>,
-<a href="r.pi.export.html">r.pi.export</a>,
-<a href="r.pi.graph.html">r.pi.graph</a>,
-<a href="r.pi.graph.dec.html">r.pi.graph.dec</a>,
-<a href="r.pi.graph.pr.html">r.pi.graph.pr</a>,
-<a href="r.pi.graph.red.html">r.pi.graph.red</a>,
-<a href="r.pi.grow.html">r.pi.grow</a>,
-<a href="r.pi.import.html">r.pi.import</a>,
-<a href="r.pi.index.html">r.pi.index</a>,
-<a href="r.pi.lm.html">r.pi.lm</a>,
-<a href="r.pi.odc.html">r.pi.odc</a>,
-<a href="r.pi.prob.mw.html">r.pi.prob.mw</a>,
-<a href="r.pi.rectangle.html">r.pi.rectangle</a>,
-<a href="r.pi.searchtime.html">r.pi.searchtime</a>,
-<a href="r.pi.searchtime.pr.html">r.pi.searchtime.pr</a>,
-<a href="r.pi.searchtime.mw.html">r.pi.searchtime.mw</a>
-<p>
-<a href="r.le.html">r.le</a>,
-<a href="r.li.html">r.li</a>
-</em>
-
-<h2>REFERENCE</h2>
-
-<ul>
-<li>Wegmann, M., Leutner, B., Metz, M., Neteler, M., Dech, S., Rocchini, D.:
-r.pi: Semi-automatic spatial pattern analysis of remotely sensed land
-cover data. Submitted.</li>
-</ul>
-
-<h2>Disclaimer</h2>
-
-This software is released under the GPL license, hence also the limitation
-of liability. This software was designed for a certain project and its research
-questions. Its nomenclature might not be concordant with other software packages.
-Moreover its capabilities are yet limited and can not be compared to such of e.g.
-Fragstats, however every user is invited to extend, modify or fix the
-functionality of <em>r.pi</em> as long as the new code comply with the GPL.
-
-<h2>AUTHORS</h2>
-Programming: Elshad Shirinov<br>
-Scientific concept: Martin Wegmann <br>
-Department of Remote Sensing <br>
-<em>Remote Sensing and Biodiversity Unit</em><br>
-University of Wuerzburg, Germany
-<p>
-Port to GRASS GIS 7: Markus Metz
-
-<p>
-<i>Last changed: $Date$</i>
Copied: grass-addons/grass7/raster/r.pi/r.pi.html (from rev 72241, grass-addons/grass7/raster/r.pi/description.html)
===================================================================
--- grass-addons/grass7/raster/r.pi/r.pi.html (rev 0)
+++ grass-addons/grass7/raster/r.pi/r.pi.html 2018-02-15 16:53:17 UTC (rev 72242)
@@ -0,0 +1,207 @@
+<h2>DESCRIPTION</h2>
+
+<em>r.pi</em> (raster patch index) provides various functions to analyse
+spatial attributes of a landscape. It has a focus on patch-based indices
+but delivers class-based indices as well. <em>r.le</em> and its successor
+<em>r.li</em> provide landscape indices.
+
+<p>
+A list with a short description of the <em>r.pi</em> modules can be found
+below. More in depth description of a certain module (commands, flags,
+options) can be found in the respective folder (like
+<em><a href="r.pi.graph.html">r.pi.graph</a></em>). The functions/algorithms
+of the modules are not yet very extensive but will be expanded in the
+future. Please submit any bug/feature you might encounter to improve the
+functionality.
+<p>
+The program will interactively query the user for input, output and
+options (GUI). However the module can be also run from the terminal
+prompt (CLI) and might be implemented in e.g. a bash-script.
+<p>
+It is highly recommended to read the help pages or e.g the overview
+documents of
+<a href="http://www.umass.edu/landeco/research/fragstats/documents/fragstats_documents.html">Fragstats</a>
+to get a better impression of problems, possibilities and caveats.
+
+
+<h2>OVERVIEW</h2>
+
+<li><em>r.pi.rectangle</em> - Performs statistical analysis on values of patches from the given raster map.
+<li><em>r.pi.energy</em> - Individual-based dispersal model for connectivity analysis - energy based.
+<li><em>r.pi.energy.pr</em> - Individual-based dispersal model for connectivity analysis (energy based) using iterative patch removal.
+<li><em>r.pi.fragment.dist</em> - Calculates correlation of two raster maps by calculating correlation function of two corresponding rectangular areas for each raster point and writing the result into a new raster map.
+<li><em>r.pi.enn</em> - Determines patches of given value and performs a nearest-neighbor analysis.
+<li><em>r.pi.index</em> - Computation of fragmentation indices.
+<li><em>r.pi.enn.pr</em> - Patch relevance for Euclidean Nearest Neighbor patches.
+<li><em>r.pi.neigh</em> - Neighbourhood analysis - value of patches within a defined range.
+<li><em>r.pi.enn</em> - Analysis of n-th Euclidean Nearest Neighbor distance.
+<li><em>r.pi.nlm</em> - Creates a random generated map with values 0 or 1by given landcover and fragment count.
+<li><em>r.pi.nlm.circ</em> - Creates a random landscape with defined attributes.
+<li><em>r.pi.nlm.stats</em> - Neutral Landscape Generator - index statistics
+<li><em>r.pi.corearea</em> - Variable edge effects and core area analysis
+<li><em>r.pi.corr.mw</em> - Moving window correlation analysis.
+<li><em>r.pi.csr.mw</em> - Complete Spatial Randomness analysis on moving window.
+<li><em>r.pi.export</em> - Export of patch based information.
+<li><em>r.pi.graph</em> - Graph Theory for connectivity analysis.
+<li><em>r.pi.graph.pr</em> - Graph Theory - iterative removal (patch relevance analysis).
+<li><em>r.pi.graph.red</em> - Graph Theory - decreasing distance threshold option.
+<li><em>r.pi.grow</em> - Size and suitability based region growing.
+<li><em>r.pi.import</em> - Import and generation of patch raster data
+<li><em>r.pi.index</em> - Basic patch based indices
+<li><em>r.pi.lm</em> - Linear regression analysis for patches.
+<li><em>r.pi.prob.mw</em> - Probability analysis of 2 random points being in the same patch.
+<li><em>r.pi.rectangle</em> - Generates a rectangle based on a corner coordinate.
+<li><em>r.pi.searchtime</em> - Individual-based dispersal model for connectivity analysis (time-based)
+<li><em>r.pi.searchtime.pr</em> - Individual-based dispersal model for connectivity analysis (time-based) using iterative removal of patches
+<li><em>r.pi.searchtime.mw</em> - Individual-based dispersal model for connectivity analysis (time-based) using moving window
+
+
+<h3>General and Connectivity Indices</h3>
+
+<ul>
+<li><b><a href="r.pi.index.html">r.pi.index</a></b>: Calculations of basic indices (area, SHAPE etc.) </li>
+<li><b><a href="r.pi.enn.html">r.pi.enn</a></b>: Area, SHAPE and distance to n-th Euclidean Nearest Neighbor</li>
+<li><b><a href="r.pi.fnn.html">r.pi.fnn</a></b>: Area, SHAPE and distance to n-th Functional Nearest Neighbor</li>
+<li><b><a href="r.pi.odc.html">r.pi.odc</a></b>: Area and distance to omnidirectional n-th Nearest Neighbors</li>
+<li><b><a href="r.pi.neigh.html">r.pi.neigh</a></b>: Extraction of values of patches in defined buffer region</li>
+<li><b><a href="r.pi.prox.html">r.pi.prox</a></b>: Calculation of Proximity and Modified Proximity Index for patches in buffer region</li>
+<li><b><a href="r.pi.graph.html">r.pi.graph</a></b>: Various connectivity indices within the Graph Theory </li>
+</ul>
+
+
+<h3>Individual-based dispersal models</h3>
+<ul>
+<li><b><a href="r.pi.searchtime.html">r.pi.searchtime</a></b>:Searchtime and Immigration rate</li>
+<li><b><a href="r.pi.energy.html">r.pi.energy</a></b>: Immigration, Migration and successfull emigration rate</li>
+<li><b><a href="r.pi.searchtime.mw.html">r.pi.searchtime.mw</a></b>:Related to <em>r.pi.searchtime</em> but using a Moving Windows approach</li>
+</ul>
+
+<h3>Patch-Relevance</h3>
+<ul>
+<li><b><a href="r.pi.enn.pr.html">r.pi.enn.pr</a></b>:Relevance of patches for maintenance of distance to first Nearest Neighbor</li>
+<li><b><a href="r.pi.searchtime.pr.html">r.pi.searchtime.pr</a></b>:Relevance of patches for maintenance of searchtime</li>
+<li><b><a href="r.pi.energy.pr.html">r.pi.energy.pr</a></b>:Relevance of patches for maintenance of immigration rate</li>
+<li><b><a href="r.pi.graph.red.html">r.pi.graph.red</a></b>:Relevance of patches ....</li>
+<li><b><a href="r.pi.graph.dec.html">r.pi.graph.dec</a></b>:Relevance of patches ....</li>
+</ul>
+
+<h3>Neutral Landscape Model</h3>
+<ul>
+<li><b><a href="r.pi.nlm.html">r.pi.nlm</a></b>: Generation of a neutral landscape (fractal)</li>
+<li><b><a href="r.pi.nlm.stats.html">r.pi.nlm.stats</a></b>:Statistical analysis of landscapes based on permutation of neutral landscapes</li>
+<li><b><a href="r.pi.nlm.circ.html">r.pi.nlm.circ</a>c</b>:Generation of a neutral landscape (circular)</li>
+</ul>
+
+<h3>Various modules</h3>
+<ul>
+<li><b><a href="r.pi.corearea.html">r.pi.corearea</a></b>:Calculation of core area based on costmatrix</li>
+<li><b><a href="r.pi.prob.mw.html">r.pi.prob.mw</a></b>:Probability of two random points being in the same patch</li>
+<li><b><a href="r.pi.rectangle.html">r.pi.rectangle</a></b>: Generation of rectangles based on coordinate points</li>
+<li><b><a href="r.pi.import.html">r.pi.import</a></b>:Import of values to corresponding patches</li>
+<li><b><a href="r.pi.export.html">r.pi.export</a></b>:Export of values from patches</li>
+<li><b><a href="r.pi.lm.html">r.pi.lm</a></b>:Residuals of a Linear Regression between 2 rasters are provided as raster</li>
+<li><b><a href="r.pi.corr.mw.html">r.pi.corr.mw</a></b>:Moving window correlation between two raster maps</li>
+</ul>
+
+<h2>EXAMPLES</h2>
+
+<h4>Calculation of the SHAPE-Index</h4>
+
+Input can be generated by <em>r.pi.nlm</em>, for example:
+
+<div class="code"><pre>
+# generate random landscape with 50% cover
+r.pi.nlm output=NLM_in landcover=50 sharpness=0.5
+
+# use the class 1 of the above generated landscape for computation of SHAPE-Index
+r.pi.index input=NLM_in keyval=1 output=NLM_in.shape method=shape
+</pre></div>
+
+
+<h4>Calculation of the distance to the first and 10th Nearest Neighbor</h4>
+
+Input generated by <em>r.pi.nlm</em>, for example:
+
+<div class="code"><pre>
+# generate random landscape with 50% cover
+r.pi.nlm output=NLM_in landcover=50 sharpness=0.5
+
+# first NN
+r.pi.index input=NLM_in keyval=1 output=NLM_in.enn1 method=ENN
+
+# 10th NN
+r.pi.enn input=NLM_in output=NLM_in.enn10 method=distance number=10
+
+# 1-10th NN
+r.pi.enn input=NLM_in output=NLM_in.enn10 method=distance number=1-10
+</pre></div>
+
+
+<h2>NOTE</h2>
+
+The maximum number of patches that can be queried at one time depend on
+the module and might also be influenced by the resolution.
+
+<h2>SEE ALSO</h2>
+
+<em>
+<a href="r.pi.corr.mw.html">r.pi.corr.mw</a>,
+<a href="r.pi.energy.html">r.pi.energy</a>,
+<a href="r.pi.energy.pr.html">r.energy.pr</a>,
+<a href="r.pi.enn.html">r.pi.enn</a>,
+<a href="r.pi.enn.pr.html">r.pi.enn.pr</a>,
+<a href="r.pi.neigh.html">r.pi.neigh</a>,
+<a href="r.pi.fnn.html">r.pi.fnn</a>,
+<a href="r.pi.nlm.circ.html">r.pi.nlm.circ</a>,
+<a href="r.pi.nlm.html">r.pi.nlm</a>,
+<a href="r.pi.nlm.stats.html">r.nlm.stats</a>,
+<a href="r.pi.corearea.html">r.pi.corearea</a>,
+<a href="r.pi.csr.mw.html">r.pi.csr.mw</a>,
+<a href="r.pi.export.html">r.pi.export</a>,
+<a href="r.pi.graph.html">r.pi.graph</a>,
+<a href="r.pi.graph.dec.html">r.pi.graph.dec</a>,
+<a href="r.pi.graph.pr.html">r.pi.graph.pr</a>,
+<a href="r.pi.graph.red.html">r.pi.graph.red</a>,
+<a href="r.pi.grow.html">r.pi.grow</a>,
+<a href="r.pi.import.html">r.pi.import</a>,
+<a href="r.pi.index.html">r.pi.index</a>,
+<a href="r.pi.lm.html">r.pi.lm</a>,
+<a href="r.pi.odc.html">r.pi.odc</a>,
+<a href="r.pi.prob.mw.html">r.pi.prob.mw</a>,
+<a href="r.pi.rectangle.html">r.pi.rectangle</a>,
+<a href="r.pi.searchtime.html">r.pi.searchtime</a>,
+<a href="r.pi.searchtime.pr.html">r.pi.searchtime.pr</a>,
+<a href="r.pi.searchtime.mw.html">r.pi.searchtime.mw</a>
+<p>
+<a href="r.le.html">r.le</a>,
+<a href="r.li.html">r.li</a>
+</em>
+
+<h2>REFERENCE</h2>
+
+<ul>
+<li>Wegmann, M., Leutner, B., Metz, M., Neteler, M., Dech, S., Rocchini, D.:
+r.pi: Semi-automatic spatial pattern analysis of remotely sensed land
+cover data. Submitted.</li>
+</ul>
+
+<h2>Disclaimer</h2>
+
+This software is released under the GPL license, hence also the limitation
+of liability. This software was designed for a certain project and its research
+questions. Its nomenclature might not be concordant with other software packages.
+Moreover its capabilities are yet limited and can not be compared to such of e.g.
+Fragstats, however every user is invited to extend, modify or fix the
+functionality of <em>r.pi</em> as long as the new code comply with the GPL.
+
+<h2>AUTHORS</h2>
+Programming: Elshad Shirinov<br>
+Scientific concept: Martin Wegmann <br>
+Department of Remote Sensing <br>
+<em>Remote Sensing and Biodiversity Unit</em><br>
+University of Wuerzburg, Germany
+<p>
+Port to GRASS GIS 7: Markus Metz
+
+<p>
+<i>Last changed: $Date$</i>
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