1r.statistics(1) Grass User's Manual r.statistics(1)
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6 r.statistics - Calculates category or object oriented statistics.
7
9 raster, statistics
10
12 r.statistics
13 r.statistics help
14 r.statistics [-c] base=name cover=name method=string output=name
15 [--overwrite] [--verbose] [--quiet]
16 Flags:
18 -c
19 Cover values extracted from the category labels of the cover map
20 --overwrite
22 Allow output files to overwrite existing files
23 --verbose
25 Verbose module output
26 --quiet
28 Quiet module output
29 Parameters:
31 base=name
32 Name of base raster map
33 cover=name
35 Name of cover raster map
36 method=string
38 Method of object-based statistic
39 Options: diversity,distribution,average,mode,median,avedev,std‐
40 dev,variance,skewness,kurtosis,min,max,sum
41 output=name
43 Resultant raster map (not used with 'distribution')
44
46 r.statistics is a tool to analyse exploratory statistics of a "cover
47 layer" according to how it intersects with objects in a "base layer".
48 A variety of standard statistical measures are possible (called "zonal
49 statistics" in some GIS). All cells in the base layer are considered
50 one object for the analysis. For some applications, one will first
51 want to prepare the input data so that all areas of contiguous cell
52 category values in the base layer are uniquely identified, which can be
53 done with r.clump.
54 The available methods are the following (english - german):
55 distribution - Verteilung in Prozent
57 average - Durchschnitt
59 mode - Modalwert
61 median - Median
63 average deviation - Durchschnittliche Abweichung
65 standard deviation - Standardabweichung
67 variance - Varianz
69 skewness - Schiefe der Verteilung
71 kurtosis - Relative Abflachung (-) oder Zuspitzung (+)
73 minimum - Minimum
75 maximum - Maximum
77 sum - Summe
79 The calculations will be performed on each area of data of the cover
80 layers which fall within each unique value, or category, of the base
81 layer.
82 Setting the -c flag the category lables of the covering raster layer
84 will be used. This is nice to avoid the GRASS limitation to interger
85 in raster maps because using category values floating point numbers can
86 be stored.
87 All calculations except "distribution" create an output layer. The
89 output layer is a reclassified version of the base layer with identical
90 category values, but modified category labels - the results of the cal‐
91 culations are stored in the category labels of the output layer.
92 For distributions, the output is printed to the user interface (std‐
94 out). If an output file name was specified, it will be ignored. The
95 result will be a text table with three columns. In the first column
96 are the category values of the base layer (a), in the second column the
97 associated value of the cover layers (b), and in the third column the
98 percentage of area in that base layer category (a) that falls into that
99 row's value in the cover layer(b). Example:
100 1 124 23
101 1 201 47
102 1 273 30
103 2 101 5
104 2 152 16
105 2 167 60
106 2 187 19
107 .
108 .
109 .
110 So for the first line in the output above, we see that 23% of the
111 cells of the base layer category 1 have a value of 124 in the cover
112 layer. To transfer the values stored as category labels into cell val‐
113 ues, r.mapcalc can be used ('@' operator).
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116 Calculation of average elevation of each field in the Spearfish region:
117 r.statistics base=fields cover=elevation.dem out=elevstats method=aver‐
118 age
119 r.category elevstats
120 r.mapcalc "fieldelev=@elevstats"
121 r.univar fieldelev
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125 r.average, r.clump, r.mode, r.median, r.mapcalc, r.neighbors, r.univar
126 r.category
127
129 Martin Schroeder, Geographisches Institut Heidelberg, Germany
130 Last changed: $Date: 2008-02-19 21:18:46 +0100 (Tue, 19 Feb 2008) $
132 Full index
134 © 2003-2008 GRASS Development Team
136GRASS 6.3.0 r.statistics(1)