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       r.kappa   -  Calculates  error  matrix  and  kappa  parameter  for  accuracy assessment of
       classification result.


       raster, statistics, classification


       r.kappa --help
       r.kappa  [-whm]   classification=name   reference=name    [output=name]     [title=string]
       [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

           Wide report
           132 columns (default: 80)

           No header in the report

           Print Matrix only

           Allow output files to overwrite existing files

           Print usage summary

           Verbose module output

           Quiet module output

           Force launching GUI dialog

       classification=name [required]
           Name of raster map containing classification result

       reference=name [required]
           Name of raster map containing reference classes

           Name for output file containing error matrix and kappa
           If not given write to standard output

           Title for error matrix and kappa
           Default: ACCURACY ASSESSMENT


       r.kappa  tabulates  the  error  matrix of classification result by crossing classified map
       layer with respect to reference  map  layer.   Both  overall  kappa  (accompanied  by  its
       variance) and conditional kappa values are calculated.  This analysis program respects the
       current geographic region and mask settings.

       r.kappa calculates the error matrix of the two map layers  and  prepares  the  table  from
       which the report is to be created.  kappa values for overall and each classes are computed
       along with their variances. Also percent of commission and ommission error, total  correct
       classified  result  by  pixel counts, total area in pixel counts and percentage of overall
       correctly classified pixels are tabulated.

       The report will be write to an output file which is in plain text format and named by user
       at prompt of running the program.

       The  body of the report is arranged in panels.  The classified result map layer categories
       is arranged along the vertical axis of the table, while the reference map layer categories
       along  the  horizontal  axis.  Each panel has a maximum of 5 categories (9 if wide format)
       across the top.  In addition, the last column of the last panel reflects a cross total  of
       each  column  for  each  row.   All  of the categories of the map layer arranged along the
       vertical axis, i.e., the reference map layer,  are included in each  panel.   There  is  a
       total at the bottom of each column representing the sum of all the rows in that column.


       It  is  recommended  to  reclassify  categories of classified result map layer into a more
       manageable number before running r.kappa on  the  classified  raster  map  layer.  Because
       r.kappa calculates and then reports information for each and every category.

       NA’s in output file mean non-applicable in case MASK exists.

       The  Estimated  kappa  value in r.kappa is the value only for one class, i.e. the observed
       agreement between the classifications for those observations that have been classified  by
       classifier 1 into the class i. In other words, here the choice of reference is important.

       It is calculated as:

       kpp[i] = (pii[i] - pi[i] * pj[i]) / (pi[i] - pi[i] * pj[i]);


           ·   pii[i]  is  the probability of agreement (i.e. number of pixels for which there is
               agreement divided by total number of assessed pixels)

           ·   Pi[i] is the probability of classification i having classified the point as i

           ·   Pj[i] is the probability of classification j having classified the point as i.


       Example for North Carolina sample dataset:
       g.region raster=landclass96 -p
       r.kappa -w classification=landuse96_28m reference=landclass96

       Verification of classified LANDSAT scene against training areas:
       r.kappa -w classification=lsat7_2002_classes reference=training


       g.region, r.category, r.mask, r.reclass,, r.stats


       Tao Wen, University of Illinois at Urbana-Champaign, Illinois

       Last changed: $Date: 2018-10-18 21:05:15 +0200 (Thu, 18 Oct 2018) $


       Available at: r.kappa source code (history)

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