1r.univar(1) Grass User's Manual r.univar(1)
2
6 r.univar - Calculates univariate statistics from the non-null cells of
7 a raster map.
8 Statistics include number of cells counted, minimum and maximum cell
9 values, range, arithmetic mean, population variance, standard devia‐
10 tion, coefficient of variation, and sum.
11
13 raster, statistics, univariate statistics, zonal statistics
14
16 r.univar
17 r.univar --help
18 r.univar [-getr] map=name[,name,...] [zones=name] [output=name]
19 [percentile=float[,float,...]] [separator=character] [--overwrite]
20 [--help] [--verbose] [--quiet] [--ui]
21 Flags:
23 -g
24 Print the stats in shell script style
25 -e
27 Calculate extended statistics
28 -t
30 Table output format instead of standard output format
31 -r
33 Use the native resolution and extent of the raster map, instead of
34 the current region
35 --overwrite
37 Allow output files to overwrite existing files
38 --help
40 Print usage summary
41 --verbose
43 Verbose module output
44 --quiet
46 Quiet module output
47 --ui
49 Force launching GUI dialog
50 Parameters:
52 map=name[,name,...]Â [required]
53 Name of raster map(s)
54 zones=name
56 Raster map used for zoning, must be of type CELL
57 output=name
59 Name for output file (if omitted or "-" output to stdout)
60 percentile=float[,float,...]
62 Percentile to calculate (requires extended statistics flag)
63 Options: 0-100
64 Default: 90
65 separator=character
67 Field separator
68 Special characters: pipe, comma, space, tab, newline
69 Default: pipe
70
72 r.univar calculates the univariate statistics of one or several raster
73 map(s). This includes the number of cells counted, minimum and maximum
74 cell values, range, arithmetic mean, population variance, standard
75 deviation, coefficient of variation, and sum. Statistics are calculated
76 separately for every category/zone found in the zones input map if
77 given. If the -e extended statistics flag is given the 1st quartile,
78 median, 3rd quartile, and given percentile are calculated. If the -g
79 flag is given the results are presented in a format suitable for use in
80 a shell script. If the -t flag is given the results are presented in
81 tabular format with the given field separator. The table can immedi‐
82 ately be converted to a vector attribute table which can then be linked
83 to a vector, e.g. the vector that was rasterized to create the zones
84 input raster.
85 When multiple input maps are given to r.univar, the overall statistics
87 are calculated. This is useful for a time series of the same variable,
88 as well as for the case of a segmented/tiled dataset. Allowing multiple
89 raster maps to be specified saves the user from using a temporary
90 raster map for the result of r.series or r.patch.
91
93 As with most GRASS raster modules, r.univar operates on the raster
94 array defined by the current region settings, not the original extent
95 and resolution of the input map. See g.region, but also the wiki page
96 on the computational region to understand the impact of the region set‐
97 tings on the calculations.
98 This module can use large amounts of system memory when the -e extended
100 statistics flag is used with a very large region setting. If the region
101 is too large the module should exit gracefully with a memory allocation
102 error. Basic statistics can be calculated using any size input region.
103 Extended statistics can be calculated using r.stats.quantile.
104 Without a zones input raster, the r.quantile module will be signifi‐
106 cantly more efficient for calculating percentiles with large maps.
107 For calculating univariate statistics from a raster map based on vector
109 polygon map and uploads statistics to new attribute columns, see
110 v.rast.stats.
111
113 Univariate statistics
114 In this example, the raster map elevation in the North Carolina sample
115 dataset is used to calculate univariate statistics:
116 g.region raster=elevation -p
117 # standard output, along with extended statistics
118 r.univar -e elevation percentile=98
119 total null and non-null cells: 2025000
120 total null cells: 0
121 Of the non-null cells:
122 ----------------------
123 n: 2025000
124 minimum: 55.5788
125 maximum: 156.33
126 range: 100.751
127 mean: 110.375
128 mean of absolute values: 110.375
129 standard deviation: 20.3153
130 variance: 412.712
131 variation coefficient: 18.4057 %
132 sum: 223510266.558102
133 1st quartile: 94.79
134 median (even number of cells): 108.88
135 3rd quartile: 126.792
136 98th percentile: 147.727
137 # script style output, along with extended statistics
138 r.univar -ge elevation percentile=98
139 n=2025000
140 null_cells=0
141 cells=2025000
142 min=55.5787925720215
143 max=156.329864501953
144 range=100.751071929932
145 mean=110.375440275606
146 mean_of_abs=110.375440275606
147 stddev=20.3153233205981
148 variance=412.712361620436
149 coeff_var=18.4056555243368
150 sum=223510266.558102
151 first_quartile=94.79
152 median=108.88
153 third_quartile=126.792
154 percentile_98=147.727
155 Zonal statistics
157 In this example, the raster polygon map basins in the North Carolina
158 sample dataset is used to calculate raster statistics for zones for
159 elevation raster map:
160 g.region raster=basins -p
161 This will set and print computational region in the format:
162 projection: 99 (Lambert Conformal Conic)
163 zone: 0
164 datum: nad83
165 ellipsoid: a=6378137 es=0.006694380022900787
166 north: 228500
167 south: 215000
168 west: 630000
169 east: 645000
170 nsres: 10
171 ewres: 10
172 rows: 1350
173 cols: 1500
174 cells: 2025000
175 Check basin’s IDs using:
176 r.category basins
177 This will print them in the format:
178 2
179 4
180 6
181 8
182 10
183 12
184 14
185 16
186 18
187 20
188 22
189 24
190 26
191 28
192 30
193 Visualization of them underlying elevation map can be created as:
194 d.mon wx0
195 d.rast map=elevation
196 r.colors map=elevation color=grey
197 d.rast map=basins
198 r.colors map=basins color=bgyr
199 d.legend raster=basins use=2,4,6,8,10,12,14,16,18,20,22,24,26,28,30
200 d.barscale
201 Figure: Zones (basins, opacity: 60%) with underlying elevation map for
202 North Carolina sample dataset.
203 Then statistics for elevation can be calculated separately for every
205 zone, i.e. basin found in the zones parameter:
206 r.univar -t map=elevation zones=basins separator=comma \
207 output=basin_elev_zonal.csv
208 This will print information in the format:
209 zone,label,non_null_cells,null_cells,min,max,range,mean,mean_of_abs,
210 stddev,variance,coeff_var,sum,sum_abs2,,116975,0,55.5787925720215,
211 133.147018432617,77.5682258605957,92.1196971445722,92.1196971445722,
212 15.1475301152556,229.447668592576,16.4433129773355,10775701.5734863,
213 10775701.57348634,,75480,0,61.7890930175781,110.348838806152,
214 48.5597457885742,83.7808205765268,83.7808205765268,11.6451777476995,
215 135.610164775515,13.8995747088232,6323776.33711624,6323776.33711624
216 6,,1137,0,66.9641571044922,83.2070922851562,16.2429351806641,
217 73.1900814395257,73.1900814395257,4.15733292896409,17.2834170822492,
218 5.68018623179036,83217.1225967407,83217.12259674078,,80506,
219 0,67.4670791625977,147.161514282227, ...
220 Comma Separated Values (CSV) file is best viewed through a spreadsheet
221 program such as Microsoft Excel, Libre/Open Office Calc or Google Docs:
222 Figure: Raster statistics for zones (basins, North Carolina sample
223 dataset) viewed through Libre/Open Office Calc.
224
226 To be implemented mode, skewness, kurtosis.
227
229 g.region, r3.univar, r.mode, r.quantile, r.series, r.stats,
230 r.stats.quantile, r.stats.zonal, r.statistics, v.rast.stats, v.univar
231
233 Hamish Bowman, Otago University, New Zealand
234 Extended statistics by Martin Landa
235 Multiple input map support by Ivan Shmakov
236 Zonal loop by Markus Metz
237
239 Available at: r.univar source code (history)
240 Main index | Raster index | Topics index | Keywords index | Graphical
242 index | Full index
243 © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual
245GRASS 7.8.2 r.univar(1)