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NAME

       r.li  - Toolset for multiscale analysis of landscape structure

KEYWORDS

       raster, landscape structure analysis, diversity index, patch index

DESCRIPTION

       The  r.li  suite  is  a toolset for multiscale analysis of landscape structure. It aims at
       implementing metrics as found in external software for quantitative measures of  landscape
       structure like FRAGSTATS (McGarigal and Marks 1995).

       The  r.li  suite  offers  a  set  of patch and diversity indices.  It supports analysis of
       landscapes composed of a mosaic of patches, but, more generally, the modules work with any
       two-dimensional  raster  map  whose cell values are integer (e.g., 1, 2) or floating point
       (e.g., 1.1, 3.2) values. The g.gui.rlisetup module has options for controlling the  shape,
       size,  number,  and  distribution  of sampling areas used to collect information about the
       landscape structure.  Sampling area shapes can be the entire map or  a  moving  window  of
       square,  rectangular or circular shape. The size of sampling areas can be changed, so that
       the landscape can be analyzed at a variety  of  spatial  scales  simultaneously.  Sampling
       areas   may   be   distributed   across   the   landscape  in  a  random,  systematic,  or
       stratified-random manner, or as a moving window.

       The r.li modules can calculate a number of measures that produce single values  as  output
       (e.g.  mean  patch  size  in  the  sampling  area),  as  well  as  measures that produce a
       distribution of values as output (e.g.  frequency  distribution  of  patch  sizes  in  the
       sampling area). The results are stored as raster maps.

       All  modules  require configuration file which can be created by the g.gui.rlisetup module
       which is a GUI tool providing a convenient way to set all necessary parameters. This  file
       can be used repetitively saving user from the need to specify all parameters over and over
       again.

NOTES

       The general procedure to calculate an index from a raster map is two-fold:

       1      run g.gui.rlisetup: create a configuration file selecting the parts of  raster  map
              to  be  analyzed.  This  file allows re-running an analysis easily. It is stored on
              Windows in the directory C:\Users\userxy\AppData\Roaming\GRASS7\r.li\, on GNU/Linux
              in $HOME/.grass7/r.li/.

       2      run  one or more of the r.li.[index] modules (e.g., r.li.patchdensity) to calculate
              the selected index using on the areas selected on configuration file.

EXAMPLES

       Calculate a patch density index on the entire ’geology’ raster map in the Spearfish sample
       dataset, using a 5x5 moving window:

       1      CREATE A NEW CONFIGURATION FILE

       1.1    run
                g.gui.rlisetup

       1.2    The main g.gui.rlisetup window is displayed, click on "New"

       1.3    The  new  configuration  window is now displayed, enter the configuration file name
              (e.g., "my_conf", do not use absolute paths) Now the new  configuration  window  is
              displayed.  Enter the configuration file name (e.g., "my_conf", do not use absolute
              paths) and the name of raster map (e.g., "geology").   The  other  fields  are  not
              needed for this configuration.

       1.4    Click on "Setup sampling frame", select "Whole map layer" and click "OK"

       1.5    Click on "Setup sampling areas", select "Moving window" and click "OK"

       1.6    Click on "Use keyboard to enter moving window dimension"

       1.7    Select "Rectangle" and enter 5 in the "height" and "width" fields

       1.8    Click on "Save settings"

       1.9    Close the g.gui.rlisetup window

       2      CALCULATE PATCHDENSITY INDEX

       2.1    set the region settings to the "geology" raster map:
                g.region raster=geology -p

       2.2    run r.li.patchdensity:
                r.li.patchdensity input=geology conf=my_conf out=patchdens

       The  resulting  patch  density  is  stored  in "patchdens" raster map.  You can verify the
       result for example with contour lines:
         r.contour in=patchdens out=patchdens step=5
         d.rast patchdens
         d.vect -c patchdens
       Note that if you want to run another index with the same  area  configuration,  you  don’t
       have  to  create another configuration file.  You can also use the same area configuration
       file on another map. The program rescale  it  automatically.  For  instance  if  you  have
       selected  a 5x5 sample area on 100x100 raster map, and you use the same configuration file
       on a 200x200 raster map, then the sample area is 10x10.

SEE ALSO

       GUI tools:

           ·   g.gui.rlisetup: Configuration editor for the r.li.* module where * is name of  the
               index
       Patch indices:

           ·   Indices based on patch number:

               ·   r.li.patchdensity:  Calculates  patch density index on a raster map, using a 4
                   neighbour algorithm

               ·   r.li.patchnum: Calculates patch number index  on  a  raster  map,  using  a  4
                   neighbour algorithm

           ·   Indices based on patch dimension:

               ·   r.li.mps:  Calculates  mean  patch  size  index  on  a  raster  map, using a 4
                   neighbour algorithm

               ·   r.li.padcv: Calculates coefficient of variation of patch area on a raster map

               ·   r.li.padrange: Calculates range of patch area size on a raster map

               ·   r.li.padsd: Calculates standard deviation of patch area a raster map

           ·   Indices based on patch shape:

               ·   r.li.shape: Calculates shape index on a raster map

           ·   Indices based on patch edge:

               ·   r.li.edgedensity: Calculates edge density index on a raster  map,  using  a  4
                   neighbour algorithm

           ·   Indices based on patch attributes:

               ·   r.li.cwed: Calculates contrast Weighted Edge Density index on a raster map

               ·   r.li.mpa: Calculates mean pixel attribute index on a raster map
       Diversity indices:

           ·   r.li.dominance: Calculates dominance diversity index on a raster map

           ·   r.li.pielou: Calculates Pielou eveness index on a raster map

           ·   r.li.renyi: Calculates Renyi entropy on a raster map

           ·   r.li.richness: Calculates richness diversity index on a raster map

           ·   r.li.shannon: Calculates Shannon diversity index on a raster map

           ·   r.li.simpson: Calculates Simpson diversity index on a raster map
       Core library:

           ·   r.li.daemon: library with common functionality (not visible to the user)

ADDING NEW INDICES

       New  indices  can  be  defined and implemented by any C programmer, without having to deal
       with all basic functions (IO etc.). The  computing  architecture  and  the  functions  are
       clearly separated, thus allowing an easy expandability. Every index is defined separately,
       placed  in  a  directory  along  with  its  Makefile  for  compiling   it   and   a   file
       <module_name>.html  which  describes  the  index  including  a  simple example of use. See
       r.li.daemon for more information about development.

REFERENCES

           ·   McGarigal, K., and B. J. Marks. 1995. FRAGSTATS: spatial pattern analysis  program
               for  quantifying  landscape  structure.  USDA  For. Serv.  Gen. Tech. Rep. PNW-351
               (PDF).

           ·   Baker, W.L. and Y. Cai.  1992.  The  r.le  programs  for  multiscale  analysis  of
               landscape  structure  using  the GRASS geographical information system.  Landscape
               Ecology 7(4):291-302.

AUTHORS

       Claudio Porta and Lucio Davide Spano, students of Computer  Science,  University  of  Pisa
       (Italy).
       Commission from Faunalia Pontedera (PI)

       Partially rewritten by Markus Metz

       Last changed: $Date: 2017-11-12 14:14:46 +0100 (Sun, 12 Nov 2017) $

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