NAME

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

KEYWORDS

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

SYNOPSIS

       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]

   Flags:
       -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

   Parameters:
       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

DESCRIPTION

       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.

NOTES

       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.

Examples

       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
       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|2012-08-24 00:00:00|1.0|3.0
       map3@PERMANENT|map3|PERMANENT|2012-08-24 00:00:00|2012-08-25 00:00:00|1.0|4.0
       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

SEE ALSO

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

AUTHOR

       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

SOURCE CODE

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

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