Provided by: grass-doc_6.4.3-3_all
r.kappa - Calculate error matrix and kappa parameter for accuracy assessment of classification result.
r.kappa r.kappa help r.kappa [-wqh] classification=name reference=name [output=name] [title=string] [--verbose] [--quiet] Flags: -w Wide report 132 columns (default: 80) -q Quiet -h No header in the report --verbose Verbose module output --quiet Quiet module output Parameters: classification=name Name of raster map containing classification result reference=name Name of raster map containing reference classes output=name Name for output file containing error matrix and kappa title=string 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.
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.report, r.stats
Tao Wen, University of Illinois at Urbana-Champaign, Illinois Last changed: $Date: 2012-12-16 04:47:36 -0800 (Sun, 16 Dec 2012) $ Full index © 2003-2013 GRASS Development Team