t.rast.gapfill - Replaces gaps in a space time
raster dataset with interpolated raster maps.
temporal, interpolation, raster, time, no-data filling
t.rast.gapfill
t.rast.gapfill --help
t.rast.gapfill [-t] input=name
[where=sql_query] basename=string
[suffix=string] [nprocs=integer] [--help]
[--verbose] [--quiet] [--ui]
- -t
-
Assign the space time raster dataset start and end time to the output
map
- --help
-
Print usage summary
- --verbose
-
Verbose module output
- --quiet
-
Quiet module output
- --ui
-
Force launching GUI dialog
- input=name [required]
-
Name of the input space time raster dataset
- where=sql_query
-
WHERE conditions of SQL statement without ’where’ keyword used
in the temporal GIS framework
Example: start_time > ’2001-01-01 12:30:00’
- basename=string [required]
-
Basename of the new generated output maps
A numerical suffix separated by an underscore will be attached to create a
unique identifier
- suffix=string
-
Suffix to add at basename: set ’gran’ for granularity,
’time’ for the full time format, ’num’ for
numerical suffix with a specific number of digits (default %05)
Default: gran
- nprocs=integer
-
Number of interpolation processes to run in parallel
Default: 1
t.rast.gapfill fills temporal gaps in space time raster
datasets using linear interpolation. Temporal all gaps will be detected in
the input space time raster dataset automatically. The predecessor and
successor maps of the gaps will be identified and used to linear interpolate
the raster map between them.
This module uses r.series.interp to perform the interpolation for
each gap independently. Hence several interpolation processes can be run in
parallel.
Each gap is re-sampled by the space time raster dataset
granularity. Therefore several time stamped raster map layers will be
interpolated if the gap is larger than the STRDS granularity.
In this example we will create 3 raster maps and register them in
the temporal database an then in the newly created space time raster
dataset. There are gaps of one and two day size between the raster maps. The
values of the maps are chosen so that the interpolated values can be
estimated. We expect one map with a value of 2 for the first gap and two
maps (values 3.666 and 4.333) for the second gap after interpolation.
r.mapcalc expression="map1 = 1"
r.mapcalc expression="map2 = 3"
r.mapcalc expression="map3 = 5"
t.register type=raster maps=map1 start=2012-08-20 end=2012-08-21
t.register type=raster maps=map2 start=2012-08-22 end=2012-08-23
t.register type=raster maps=map3 start=2012-08-25 end=2012-08-26
t.create type=strds temporaltype=absolute \
output=precipitation_daily \
title="Daily precipitation" \
description="Test dataset with daily precipitation"
t.register type=raster input=precipitation_daily maps=map1,map2,map3
# the output shows three missing maps
t.rast.list input=precipitation_daily columns=name,start_time,min,max
name|start_time|min|max
map1|2012-08-20 00:00:00|1.0|1.0
map2|2012-08-22 00:00:00|3.0|3.0
map3|2012-08-25 00:00:00|5.0|5.0
t.rast.list input=precipitation_daily method=deltagaps
id|name|mapset|start_time|end_time|interval_length|distance_from_begin
map1@PERMANENT|map1|PERMANENT|2012-08-20 00:00:00|2012-08-21 00:00:00|1.0|0.0
None|None|None|2012-08-21 00:00:00|2012-08-22 00:00:00|1.0|1.0
map2@PERMANENT|map2|PERMANENT|2012-08-22 00:00:00|2012-08-23 00:00:00|1.0|2.0
None|None|None|2012-08-23 00:00:00|2012-08-25 00:00:00|2.0|3.0
map3@PERMANENT|map3|PERMANENT|2012-08-25 00:00:00|2012-08-26 00:00:00|1.0|5.0
t.rast.gapfill input=precipitation_daily basename=gap
t.rast.list input=precipitation_daily columns=name,start_time,min,max
name|start_time|min|max
map1|2012-08-20 00:00:00|1.0|1.0
gap_6_1|2012-08-21 00:00:00|2.0|2.0
map2|2012-08-22 00:00:00|3.0|3.0
gap_7_1|2012-08-23 00:00:00|3.666667|3.666667
gap_7_2|2012-08-24 00:00:00|4.333333|4.333333
map3|2012-08-25 00:00:00|5.0|5.0
r.series.interp, t.create, t.info
Sören Gebbert, Thünen Institute of Climate-Smart
Agriculture
Available at: t.rast.gapfill source code (history)
Latest change: Thursday Jan 26 14:10:26 2023 in commit:
cdd84c130cea04b204479e2efdc75c742efc4843
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