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NAME

       r.statistics  - Calculates category or object oriented statistics.

KEYWORDS

       raster, statistics, zonal statistics

SYNOPSIS

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

   Flags:
       -c
           Cover values extracted from the category labels of the cover map

       --overwrite
           Allow output files to overwrite existing files

       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:
       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

DESCRIPTION

       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.

NOTES

       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 r.stats.quantile.

EXAMPLES

       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

SEE ALSO

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

AUTHOR

       Martin Schroeder, Geographisches Institut Heidelberg, Germany

SOURCE CODE

       Available at: r.statistics source code (history)

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       © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual