1r.series.accumulate(1) GRASS GIS User's Manual r.series.accumulate(1)
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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.
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11 raster, series, accumulation
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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]
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21 Flags:
22 -n
23 Propagate NULLs
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25 -z
26 Do not keep files open
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28 -f
29 Create a FCELL map (floating point single precision) as output
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31 --overwrite
32 Allow output files to overwrite existing files
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34 --help
35 Print usage summary
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37 --verbose
38 Verbose module output
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40 --quiet
41 Quiet module output
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43 --ui
44 Force launching GUI dialog
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46 Parameters:
47 basemap=name
48 Existing map to be added to output
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50 input=name[,name,...]
51 Name of input raster map(s)
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53 file=name
54 Input file with raster map names, one per line
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56 output=name [required]
57 Name for output raster map
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59 scale=float
60 Scale factor for input
61 Default: 1.0
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63 shift=float
64 Shift factor for input
65 Default: 0.0
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67 lower=name
68 The raster map specifying the lower accumulation limit, also called
69 baseline
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71 upper=name
72 The raster map specifying the upper accumulation limit, also called
73 cutoff. Only applied to BEDD computation.
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75 range=min,max
76 Ignore values outside this range
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78 limits=lower,upper
79 Use these limits in case lower and/or upper input maps are not de‐
80 fined
81 Default: 10,30
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83 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)
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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.
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101 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)
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107 GDD Growing Degree Days are calculated as
108 gdd = average - lower
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110 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).
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115 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.
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120 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).
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126 Mean raster values are calculated as
127 mean = average
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129 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 au‐
131 tomatically calculated from the input maps.
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133 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.
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138 If an existing map is provided with the basemap option, the values of
139 this map are added to the output.
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142 The scale and shift parameters are used to transform input values with
143 new = old * scale + shift
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145 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.
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149 Negative results are set to 0 (zero).
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151 Without the -n flag, all non-NULL cells are used for calculation.
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153 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 re‐
158 sult 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).
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163 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 su‐
168 peruser 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.
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177 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 op‐
180 tion is slower than with the input option. For every single row in the
181 output map(s) all input maps are opened and closed. The amount of RAM
182 will rise linearly with the number of specified input maps. The input
183 and file options are mutually exclusive: the former is a comma sepa‐
184 rated list of raster map names and the latter is a text file with a new
185 line separated list of raster map names.
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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
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194 g.list, g.region, r.series, r.series.interp
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196 Hints for large raster data processing
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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.
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204 Markus Metz and Soeren Gebbert (based on r.series)
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207 Available at: r.series.accumulate source code (history)
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209 Accessed: Mon Jun 20 16:46:25 2022
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211 Main index | Raster index | Topics index | Keywords index | Graphical
212 index | Full index
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214 © 2003-2022 GRASS Development Team, GRASS GIS 8.2.0 Reference Manual
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218GRASS 8.2.0 r.series.accumulate(1)