Ubuntu Manpage: r.kappa - Calculates error matrix and kappa parameter for accuracy assessment of

Provided by: grass-doc_7.8.2-1build3_all

NAME

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

KEYWORDS

       raster, statistics, classification

SYNOPSIS

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

   Flags:
       -w
           Wide report
           132 columns (default: 80)

       -h
           No header in the report

       -m
           Print Matrix only

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

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

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

       title=string
           Title for error matrix and kappa
           Default: ACCURACY ASSESSMENT

DESCRIPTION

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.

NOTES

       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]);

       where=

           •   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

       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

AUTHOR

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

SOURCE CODE

       Available at: r.kappa source code (history)

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