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       r.statistics  - Calculates category or object oriented statistics.


       raster, statistics, zonal statistics


       r.statistics --help
       r.statistics  [-c] base=name cover=name method=string output=name  [--overwrite]  [--help]
       [--verbose]  [--quiet]  [--ui]

           Cover values extracted from the category labels of the cover map

           Allow output files to overwrite existing files

           Print usage summary

           Verbose module output

           Quiet module output

           Force launching GUI dialog

       base=name [required]
           Name of base raster map

       cover=name [required]
           Name of cover raster map

       method=string [required]
           Method of object-based statistic
           Options:  diversity,  average,  mode,  median,  avedev,  stddev,  variance,  skewness,
           kurtosis, min, max, sum
           diversity: Diversity of values in specified objects in %%
           average: Average of values in specified objects
           mode: Mode of values in specified objects
           median: Median of values in specified objects
           avedev: Average deviation of values in specified objects
           stddev: Standard deviation of values in specified objects
           variance: Variance of values in specified objects
           skewness: Skewnes of values in specified objects
           kurtosis: Kurtosis of values in specified objects
           min: Minimum of values in specified objects
           max: Maximum of values in specified objects
           sum: Sum of values in specified objects

       output=name [required]
           Resultant raster map


       r.statistics  is  a  tool to analyse exploratory statistics of a categorical "cover layer"
       according to how it intersects with objects in a "base  layer".   A  variety  of  standard
       statistical  measures  are possible (called "zonal statistics" in some GIS).  All cells in
       the base layer are considered one object for the analysis.   For  some  applications,  one
       will  first  want  to prepare the input data so that all areas of contiguous cell category
       values in the base layer are uniquely identified, which can be done with r.clump.
       The available methods are the following:

           ·   average deviation

           ·   average

           ·   diversity

           ·   kurtosis

           ·   maximum

           ·   median

           ·   minimum

           ·   mode

           ·   skewness

           ·   standard deviation

           ·   sum

           ·   variance
       The calculations will be performed on each area of data of the  cover  layers  which  fall
       within each unique value, or category, of the base layer.

       Setting  the  -c flag the category labels of the covering raster layer will be used.  This
       is nice to avoid the GRASS limitation to integer in raster  maps  because  using  category
       values floating point numbers can be stored.

       All  calculations  create  an output layer.  The output layer is a reclassified version of
       the base layer with identical category values, but modified category labels - the  results
       of the calculations are stored in the category labels of the output layer.


       For  floating-point  cover  map  support, see the alternative r.stats.zonal.  For quantile
       calculations  with  support  for  floating-point   cover   maps,   see   the   alternative


       Calculation of average elevation of each field in the Spearfish region:
       r.statistics base=fields cover=elevation.dem out=elevstats method=average
       r.category elevstats
       r.mapcalc "fieldelev = @elevstats"
       r.univar fieldelev


         r.category,  r.clump,  r.mode,  r.mapcalc, r.neighbors, r.stats.quantile, r.stats.zonal,


       Martin Schroeder, Geographisches Institut Heidelberg, Germany

       Last changed: $Date: 2017-01-19 14:35:33 +0100 (Thu, 19 Jan 2017) $


       Available at: r.statistics source code (history)

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