t.rast.gapfill(1grass)

1t.rast.gapfill(1)             Grass 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
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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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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       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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AUTHOR

121       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
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123       Last changed: $Date: 2015-09-22 10:10:38 +0200 (Tue, 22 Sep 2015) $
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SOURCE CODE

126       Available at: t.rast.gapfill source code (history)
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128       Main index | Temporal index | Topics index | Keywords index | Graphical
129       index | Full index
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131       © 2003-2019 GRASS Development Team, GRASS GIS 7.6.0 Reference Manual
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135GRASS 7.6.0                                                  t.rast.gapfill(1)