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


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 --help
t.rast.gapfill [-t] input=name [where=sql_query] basename=string [suffix=string] [nprocs=integer] [--help] [--verbose] [--quiet] [--ui]


Assign the space time raster dataset start and end time to the output map

Print usage summary

Verbose module output

Quiet module output

Force launching GUI dialog


Name of the input space time raster dataset

WHERE conditions of SQL statement without ’where’ keyword used in the temporal GIS framework
Example: start_time > ’2001-01-01 12:30:00’

Basename of the new generated output maps
A numerical suffix separated by an underscore will be attached to create a unique identifier

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

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,


Sören Gebbert, Thünen Institute of Climate-Smart Agriculture


Available at: t.rast.gapfill source code (history)

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