1t.rast.series(1) GRASS GIS User's Manual t.rast.series(1)
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6 t.rast.series - Performs different aggregation algorithms from
7 r.series on all or a subset of raster maps in a space time raster
8 dataset.
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11 temporal, aggregation, series, raster, time
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14 t.rast.series
15 t.rast.series --help
16 t.rast.series [-tn] input=name method=string[,string,...] [quan‐
17 tile=float[,float,...]] [order=string[,string,...]]
18 [where=sql_query] output=name[,name,...] [--overwrite] [--help]
19 [--verbose] [--quiet] [--ui]
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21 Flags:
22 -t
23 Do not assign the space time raster dataset start and end time to
24 the output map
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26 -n
27 Propagate NULLs
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29 --overwrite
30 Allow output files to overwrite existing files
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32 --help
33 Print usage summary
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35 --verbose
36 Verbose module output
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38 --quiet
39 Quiet module output
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41 --ui
42 Force launching GUI dialog
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44 Parameters:
45 input=name [required]
46 Name of the input space time raster dataset
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48 method=string[,string,...]Â [required]
49 Aggregate operation to be performed on the raster maps
50 Options: average, count, median, mode, minimum, min_raster, maxi‐
51 mum, max_raster, stddev, range, sum, variance, diversity, slope,
52 offset, detcoeff, quart1, quart3, perc90, quantile, skewness, kur‐
53 tosis
54 Default: average
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56 quantile=float[,float,...]
57 Quantile to calculate for method=quantile
58 Options: 0.0-1.0
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60 order=string[,string,...]
61 Sort the maps by category
62 Options: id, name, creator, mapset, creation_time, modifica‐
63 tion_time, start_time, end_time, north, south, west, east,
64 min, max
65 Default: start_time
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67 where=sql_query
68 WHERE conditions of SQL statement without ’where’ keyword used in
69 the temporal GIS framework
70 Example: start_time > ’2001-01-01 12:30:00’
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72 output=name[,name,...]Â [required]
73 Name for output raster map(s)
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76 The input of this module is a single space time raster dataset, the
77 output is a single raster map layer. A subset of the input space time
78 raster dataset can be selected using the where option. The sorting of
79 the raster map layer can be set using the order option. Be aware that
80 the order of the maps can significantly influence the result of the
81 aggregation (e.g.: slope). By default the maps are ordered by
82 start_time.
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84 t.rast.series is a simple wrapper for the raster module r.series. It
85 supports a subset of the aggregation methods of r.series.
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88 Estimate the average temperature for the whole time series
89 Here the entire stack of input maps is considered:
90 t.rast.series input=tempmean_monthly output=tempmean_average method=average
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92 Estimate the average temperature for a subset of the time series
93 Here the stack of input maps is limited to a certain period of time:
94 t.rast.series input=tempmean_daily output=tempmean_season method=average \
95 where="start_time >= ’2012-06’ and start_time <= ’2012-08’"
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97 Climatology: single month in a multi-annual time series
98 By considering only a single month in a multi-annual time series the
99 so-called climatology can be computed. Estimate average temperature
100 for all January maps in the time series:
101 t.rast.series input=tempmean_monthly \
102 method=average output=tempmean_january \
103 where="strftime(’%m’, start_time)=’01’"
104 # equivalently, we can use
105 t.rast.series input=tempmean_monthly \
106 output=tempmean_january method=average \
107 where="start_time = datetime(start_time, ’start of year’, ’0 month’)"
108 # if we want also February and March averages
109 t.rast.series input=tempmean_monthly \
110 output=tempmean_february method=average \
111 where="start_time = datetime(start_time, ’start of year’, ’1 month’)"
112 t.rast.series input=tempmean_monthly \
113 output=tempmean_march method=average \
114 where="start_time = datetime(start_time, ’start of year’, ’2 month’)"
115 Generalizing a bit, we can estimate monthly climatologies for all
116 months by means of different methods
117 for i in `seq -w 1 12` ; do
118 for m in average stddev minimum maximum ; do
119 t.rast.series input=tempmean_monthly method=${m} output=tempmean_${m}_${i} \
120 where="strftime(’%m’, start_time)=’${i}’"
121 done
122 done
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125 r.series, t.create, t.info
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127 Temporal data processing Wiki
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130 Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
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133 Available at: t.rast.series source code (history)
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135 Main index | Temporal 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 t.rast.series(1)