1t.rast.gapfill(1) Grass User's Manual t.rast.gapfill(1)
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6 t.rast.gapfill - Replaces gaps in a space time raster dataset with
7 interpolated raster maps.
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10 temporal, interpolation, raster, time, no-data filling
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13 t.rast.gapfill
14 t.rast.gapfill --help
15 t.rast.gapfill [-t] input=name [where=sql_query] basename=string
16 [suffix=string] [nprocs=integer] [--help] [--verbose] [--quiet]
17 [--ui]
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19 Flags:
20 -t
21 Assign the space time raster dataset start and end time to the out‐
22 put map
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24 --help
25 Print usage summary
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27 --verbose
28 Verbose module output
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30 --quiet
31 Quiet module output
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33 --ui
34 Force launching GUI dialog
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36 Parameters:
37 input=name [required]
38 Name of the input space time raster dataset
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40 where=sql_query
41 WHERE conditions of SQL statement without ’where’ keyword used in
42 the temporal GIS framework
43 Example: start_time > ’2001-01-01 12:30:00’
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45 basename=string [required]
46 Basename of the new generated output maps
47 A numerical suffix separated by an underscore will be attached to
48 create a unique identifier
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50 suffix=string
51 Suffix to add at basename: set ’gran’ for granularity, ’time’ for
52 the full time format, ’num’ for numerical suffix with a specific
53 number of digits (default %05)
54 Default: gran
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56 nprocs=integer
57 Number of interpolation processes to run in parallel
58 Default: 1
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61 t.rast.gapfill fills temporal gaps in space time raster datasets using
62 linear interpolation. Temporal all gaps will be detected in the input
63 space time raster dataset automatically. The predecessor and successor
64 maps of the gaps will be identified and used to linear interpolate the
65 raster map between them.
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68 This module uses r.series.interp to perform the interpolation for each
69 gap independently. Hence several interpolation processes can be run in
70 parallel.
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72 Each gap is re-sampled by the space time raster dataset granularity.
73 Therefore several time stamped raster map layers will be interpolated
74 if the gap is larger than the STRDS granularity.
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77 In this example we will create 3 raster maps and register them in the
78 temporal database an then in the newly created space time raster
79 dataset. There are gaps of one and two day size between the raster
80 maps. The values of the maps are chosen so that the interpolated values
81 can be estimated. We expect one map with a value of 2 for the first
82 gap and two maps (values 3.666 and 4.333) for the second gap after
83 interpolation.
84 r.mapcalc expression="map1 = 1"
85 r.mapcalc expression="map2 = 3"
86 r.mapcalc expression="map3 = 5"
87 t.register type=raster maps=map1 start=2012-08-20 end=2012-08-21
88 t.register type=raster maps=map2 start=2012-08-22 end=2012-08-23
89 t.register type=raster maps=map3 start=2012-08-25 end=2012-08-26
90 t.create type=strds temporaltype=absolute \
91 output=precipitation_daily \
92 title="Daily precipitation" \
93 description="Test dataset with daily precipitation"
94 t.register type=raster input=precipitation_daily maps=map1,map2,map3
95 t.rast.list input=precipitation_daily columns=name,start_time,min,max
96 name|start_time|min|max
97 map1|2012-08-20 00:00:00|1.0|1.0
98 map2|2012-08-22 00:00:00|3.0|3.0
99 map3|2012-08-25 00:00:00|5.0|5.0
100 t.rast.list input=precipitation_daily method=deltagaps
101 id|name|mapset|start_time|end_time|interval_length|distance_from_begin
102 map1@PERMANENT|map1|PERMANENT|2012-08-20 00:00:00|2012-08-21 00:00:00|1.0|0.0
103 None|None|None|2012-08-21 00:00:00|2012-08-22 00:00:00|1.0|1.0
104 map2@PERMANENT|map2|PERMANENT|2012-08-22 00:00:00|2012-08-23 00:00:00|1.0|2.0
105 None|None|None|2012-08-23 00:00:00|2012-08-24 00:00:00|1.0|3.0
106 map3@PERMANENT|map3|PERMANENT|2012-08-24 00:00:00|2012-08-25 00:00:00|1.0|4.0
107 t.rast.gapfill input=precipitation_daily basename=gap
108 t.rast.list input=precipitation_daily columns=name,start_time,min,max
109 name|start_time|min|max
110 map1|2012-08-20 00:00:00|1.0|1.0
111 gap_6_1|2012-08-21 00:00:00|2.0|2.0
112 map2|2012-08-22 00:00:00|3.0|3.0
113 gap_7_1|2012-08-23 00:00:00|3.666667|3.666667
114 gap_7_2|2012-08-24 00:00:00|4.333333|4.333333
115 map3|2012-08-25 00:00:00|5.0|5.0
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118 r.series.interp, t.create, t.info
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121 Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
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124 Available at: t.rast.gapfill source code (history)
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126 Main index | Temporal index | Topics index | Keywords index | Graphical
127 index | Full index
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129 © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual
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133GRASS 7.8.2 t.rast.gapfill(1)