1t.rast.gapfill(1)           GRASS GIS User's Manual          t.rast.gapfill(1)
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NAME

6       t.rast.gapfill   -  Replaces  gaps  in a space time raster dataset with
7       interpolated raster maps.
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KEYWORDS

10       temporal, interpolation, raster, time, no-data filling
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SYNOPSIS

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]
18
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
26
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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DESCRIPTION

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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NOTES

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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Examples

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       # the output shows three missing maps
96       t.rast.list input=precipitation_daily columns=name,start_time,min,max
97       name|start_time|min|max
98       map1|2012-08-20 00:00:00|1.0|1.0
99       map2|2012-08-22 00:00:00|3.0|3.0
100       map3|2012-08-25 00:00:00|5.0|5.0
101       t.rast.list input=precipitation_daily method=deltagaps
102       id|name|mapset|start_time|end_time|interval_length|distance_from_begin
103       map1@PERMANENT|map1|PERMANENT|2012-08-20 00:00:00|2012-08-21 00:00:00|1.0|0.0
104       None|None|None|2012-08-21 00:00:00|2012-08-22 00:00:00|1.0|1.0
105       map2@PERMANENT|map2|PERMANENT|2012-08-22 00:00:00|2012-08-23 00:00:00|1.0|2.0
106       None|None|None|2012-08-23 00:00:00|2012-08-25 00:00:00|2.0|3.0
107       map3@PERMANENT|map3|PERMANENT|2012-08-25 00:00:00|2012-08-26 00:00:00|1.0|5.0
108       t.rast.gapfill input=precipitation_daily basename=gap
109       t.rast.list input=precipitation_daily columns=name,start_time,min,max
110       name|start_time|min|max
111       map1|2012-08-20 00:00:00|1.0|1.0
112       gap_6_1|2012-08-21 00:00:00|2.0|2.0
113       map2|2012-08-22 00:00:00|3.0|3.0
114       gap_7_1|2012-08-23 00:00:00|3.666667|3.666667
115       gap_7_2|2012-08-24 00:00:00|4.333333|4.333333
116       map3|2012-08-25 00:00:00|5.0|5.0
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SEE ALSO

119        r.series.interp, t.create, t.info
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AUTHOR

122       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
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SOURCE CODE

125       Available at: t.rast.gapfill source code (history)
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127       Main index | Temporal index | Topics index | Keywords index | Graphical
128       index | Full index
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130       © 2003-2020 GRASS Development Team, GRASS GIS 7.8.5 Reference Manual
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134GRASS 7.8.5                                                  t.rast.gapfill(1)