r.kappa(1grass) GRASS GIS User's Manual r.kappa(1grass)
NAME
r.kappa - Calculates error matrix and kappa parameter for accuracy as-
sessment of classification result.
KEYWORDS
raster, statistics, classification
SYNOPSIS
r.kappa
r.kappa --help
r.kappa [-whm] classification=name reference=name [output=name] [ti-
tle=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 re-
gion 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 comission and omission error, total correct classified re-
sult 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 for-
mat 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 clas-
sified 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 ob-
servations 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 as-
sessed 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
# export Kappa matrix as CSV file "kappa.csv"
r.kappa classification=landuse96_28m reference=landclass96 output=kappa.csv -m -h
Verification of classified LANDSAT scene against training areas:
r.kappa -w classification=lsat7_2002_classes reference=training
SEE ALSO
g.region, r.category, r.mask, r.reclass, r.report, r.stats
AUTHOR
Tao Wen, University of Illinois at Urbana-Champaign, Illinois
SOURCE CODE
Available at: r.kappa source code (history)
Accessed: unknown
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