1r.kappa(1) GRASS GIS User's Manual r.kappa(1)
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6 r.kappa - Calculates error matrix and kappa parameter for accuracy
7 assessment of classification result.
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10 raster, statistics, classification
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13 r.kappa
14 r.kappa --help
15 r.kappa [-whm] classification=name reference=name [output=name]
16 [title=string] [--overwrite] [--help] [--verbose] [--quiet]
17 [--ui]
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19 Flags:
20 -w
21 Wide report
22 132 columns (default: 80)
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24 -h
25 No header in the report
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27 -m
28 Print Matrix only
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30 --overwrite
31 Allow output files to overwrite existing files
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33 --help
34 Print usage summary
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36 --verbose
37 Verbose module output
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39 --quiet
40 Quiet module output
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42 --ui
43 Force launching GUI dialog
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45 Parameters:
46 classification=name [required]
47 Name of raster map containing classification result
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49 reference=name [required]
50 Name of raster map containing reference classes
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52 output=name
53 Name for output file containing error matrix and kappa
54 If not given write to standard output
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56 title=string
57 Title for error matrix and kappa
58 Default: ACCURACY ASSESSMENT
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61 r.kappa tabulates the error matrix of classification result by crossing
62 classified map layer with respect to reference map layer. Both overall
63 kappa (accompanied by its variance) and conditional kappa values are
64 calculated. This analysis program respects the current geographic
65 region and mask settings.
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67 r.kappa calculates the error matrix of the two map layers and prepares
68 the table from which the report is to be created. kappa values for
69 overall and each classes are computed along with their variances. Also
70 percent of comission and omission error, total correct classified
71 result by pixel counts, total area in pixel counts and percentage of
72 overall correctly classified pixels are tabulated.
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74 The report will be write to an output file which is in plain text for‐
75 mat and named by user at prompt of running the program.
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77 The body of the report is arranged in panels. The classified result
78 map layer categories is arranged along the vertical axis of the table,
79 while the reference map layer categories along the horizontal axis.
80 Each panel has a maximum of 5 categories (9 if wide format) across the
81 top. In addition, the last column of the last panel reflects a cross
82 total of each column for each row. All of the categories of the map
83 layer arranged along the vertical axis, i.e., the reference map layer,
84 are included in each panel. There is a total at the bottom of each
85 column representing the sum of all the rows in that column.
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88 It is recommended to reclassify categories of classified result map
89 layer into a more manageable number before running r.kappa on the clas‐
90 sified raster map layer. Because r.kappa calculates and then reports
91 information for each and every category.
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93 NA’s in output file mean non-applicable in case MASK exists.
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95 The Estimated kappa value in r.kappa is the value only for one class,
96 i.e. the observed agreement between the classifications for those
97 observations that have been classified by classifier 1 into the class
98 i. In other words, here the choice of reference is important.
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100 It is calculated as:
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102 kpp[i] = (pii[i] - pi[i] * pj[i]) / (pi[i] - pi[i] * pj[i]);
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104 where=
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106 · pii[i] is the probability of agreement (i.e. number of pixels
107 for which there is agreement divided by total number of
108 assessed pixels)
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110 · Pi[i] is the probability of classification i having classified
111 the point as i
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113 · Pj[i] is the probability of classification j having classified
114 the point as i.
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117 Example for North Carolina sample dataset:
118 g.region raster=landclass96 -p
119 r.kappa -w classification=landuse96_28m reference=landclass96
120 # export Kappa matrix as CSV file "kappa.csv"
121 r.kappa classification=landuse96_28m reference=landclass96 output=kappa.csv -m -h
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123 Verification of classified LANDSAT scene against training areas:
124 r.kappa -w classification=lsat7_2002_classes reference=training
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127 g.region, r.category, r.mask, r.reclass, r.report, r.stats
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130 Tao Wen, University of Illinois at Urbana-Champaign, Illinois
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133 Available at: r.kappa source code (history)
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135 Main index | Raster index | Topics index | Keywords index | Graphical
136 index | Full index
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138 © 2003-2020 GRASS Development Team, GRASS GIS 7.8.5 Reference Manual
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142GRASS 7.8.5 r.kappa(1)