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 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.
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=
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
Available at: r.kappa source code (history)
Latest change: Friday Mar 20 09:33:18 2020 in commit: 87ff7187f5a2ba6eda4ca43a0e97158013610401
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