1r.series.accumulate(1) Grass User's Manual r.series.accumulate(1)
2
6 r.series.accumulate - Makes each output cell value a accumulationfunc‐
7 tion of the values assigned to the corresponding cells in the input
8 raster map layers.
9
11 raster, series, accumulation
12
14 r.series.accumulate
15 r.series.accumulate --help
16 r.series.accumulate [-nzf] [basemap=name] [input=name[,name,...]]
17 [file=name] output=name [scale=float] [shift=float] [lower=name]
18 [upper=name] [range=min,max] [limits=lower,upper] [method=string]
19 [--overwrite] [--help] [--verbose] [--quiet] [--ui]
20 Flags:
22 -n
23 Propagate NULLs
24 -z
26 Do not keep files open
27 -f
29 Create a FCELL map (floating point single precision) as output
30 --overwrite
32 Allow output files to overwrite existing files
33 --help
35 Print usage summary
36 --verbose
38 Verbose module output
39 --quiet
41 Quiet module output
42 --ui
44 Force launching GUI dialog
45 Parameters:
47 basemap=name
48 Existing map to be added to output
49 input=name[,name,...]
51 Name of input raster map(s)
52 file=name
54 Input file with raster map names, one per line
55 output=name [required]
57 Name for output raster map
58 scale=float
60 Scale factor for input
61 Default: 1.0
62 shift=float
64 Shift factor for input
65 Default: 0.0
66 lower=name
68 The raster map specifying the lower accumulation limit, also called
69 baseline
70 upper=name
72 The raster map specifying the upper accumulation limit, also called
73 cutoff. Only applied to BEDD computation.
74 range=min,max
76 Ignore values outside this range
77 limits=lower,upper
79 Use these limits in case lower and/or upper input maps are not
80 defined
81 Default: 10,30
82 method=string
84 This method will be applied to compute the accumulative values from
85 the input maps
86 Options: gdd, bedd, huglin, mean
87 Default: gdd
88 gdd: Growing Degree Days or Winkler indices
89 bedd: Biologically Effective Degree Days
90 huglin: Huglin Heliothermal index
91 mean: Mean: sum(input maps)/(number of input maps)
92
94 r.series.accumulate calculates (accumulated) raster value using growing
95 degree days (GDDs)/Winkler indices’s, Biologically Effective Degree
96 Days (BEDD), Huglin heliothermal indices or an average approach from
97 several input maps for a given day. Accumulation of e.g. degree-days
98 to growing degree days (GDDs) can be done by providing a basemap with
99 GDDs of the previous day.
100 The flag -a determines the average computation of the input raster
102 maps. In case the flag is not set, the average calculation is:
103 average = (min + max) / 2
104 In case the flag was set, the calculation changes to arithmetic mean
105 average = sum(input maps) / (number of input maps)
106 GDD Growing Degree Days are calculated as
108 gdd = average - lower
109 In case the -a is set, the Winkler indices are calculated instead of
111 GDD, usually accumulated for the period April 1st to October 31st
112 (northern hemisphere) or the period October 1st to April 30th (southern
113 hemisphere).
114 BEDDs Biologically Effective Degree Days are calculated as
116 bedd = average - lower
117 with an optional upper cutoff applied to the average instead of the
118 temperature values.
119 The Huglin heliothermal index is calculated as
121 huglin = (average + max) / 2 - lower
122 usually accumulated for the period April 1st to September 30th (north‐
123 ern hemisphere) or the period September 1st to April 30th (southern
124 hemisphere).
125 Mean raster values are calculated as
127 mean = average
128 For all the formulas min is the minimum value, max the maximum value
130 and average the average value. The min, max and average values are
131 automatically calculated from the input maps.
132 The shift and scale values are applied directly to the input values.
134 The lower and upper maps, as well as the range options are applied to
135 constrain the accumulation. In case the lower and upper maps are not
136 provided the limits option with default values will be applied.
137 If an existing map is provided with the basemap option, the values of
139 this map are added to the output.
140
142 The scale and shift parameters are used to transform input values with
143 new = old * scale + shift
144 With the -n flag, any cell for which any of the corresponding input
146 cells are NULL is automatically set to NULL (NULL propagation) and the
147 accumulated value is not calculated.
148 Negative results are set to 0 (zero).
150 Without the -n flag, all non-NULL cells are used for calculation.
152 If the range= option is given, any values which fall outside that range
154 will be treated as if they were NULL. Note that the range is applied to
155 the scaled and shifted input data. The range parameter can be set to
156 low,high thresholds: values outside of this range are treated as NULL
157 (i.e., they will be ignored by most aggregates, or will cause the
158 result to be NULL if -n is given). The low,high thresholds are floating
159 point, so use -inf or inf for a single threshold (e.g., range=0,inf to
160 ignore negative values, or range=-inf,-200.4 to ignore values above
161 -200.4).
162 The maximum number of raster maps that can be processed is given by the
164 user-specific limit of the operating system. For example, the soft lim‐
165 its for users are typically 1024 files. The soft limit can be changed
166 with e.g. ulimit -n 4096 (UNIX-based operating systems) but it cannot
167 be higher than the hard limit. If the latter is too low, you can as
168 superuser add an entry in:
169 /etc/security/limits.conf
170 # <domain> <type> <item> <value>
171 your_username hard nofile 4096
172 This will raise the hard limit to 4096 files. Also have a look at the
173 overall limit of the operating system
174 cat /proc/sys/fs/file-max
175 which on modern Linux systems is several 100,000 files.
176 Use the -z flag to analyze large amounts of raster maps without hitting
178 open files limit and the file option to avoid hitting the size limit of
179 command line arguments. Note that the computation using the file
180 option is slower than with the input option. For every single row in
181 the output map(s) all input maps are opened and closed. The amount of
182 RAM will rise linearly with the number of specified input maps. The
183 input and file options are mutually exclusive: the former is a comma
184 separated list of raster map names and the latter is a text file with a
185 new line separated list of raster map names.
186
188 Example with MODIS Land Surface Temperature, transforming values from
189 Kelvin * 50 to degrees Celsius:
190 r.series.accumulate in=MOD11A1.Day,MOD11A1.Night,MYD11A1.Day,MYD11A1.Night out=MCD11A1.GDD \
191 scale=0.02 shift=-273.15 limits=10,30
192
194 g.list, g.region, r.series, r.series.interp
195 Hints for large raster data processing
197
199 · Jones, G.V., Duff, A.A., Hall, A., Myers, J.W., 2010. Spatial
200 analysis of climate in winegrape growing regions in the Western
201 United States. Am. J. Enol. Vitic. 61, 313-326.
202
204 Markus Metz and Soeren Gebbert (based on r.series)
205 Last changed: $Date: 2018-02-11 22:29:12 +0100 (Sun, 11 Feb 2018) $
207
209 Available at: r.series.accumulate source code (history)
210 Main index | Raster index | Topics index | Keywords index | Graphical
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213 © 2003-2019 GRASS Development Team, GRASS GIS 7.6.0 Reference Manual
215GRASS 7.6.0 r.series.accumulate(1)