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

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)

       Main index | Raster index | Topics index | Keywords index | Graphical index | Full index

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