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NAME

       t.rast.neighbors   -  Performs a neighborhood analysis for each map in a space time raster
       dataset.

KEYWORDS

       temporal, aggregation, raster, time

SYNOPSIS

       t.rast.neighbors
       t.rast.neighbors --help
       t.rast.neighbors  [-nr]   input=name   output=name    [where=sql_query]     [size=integer]
       method=string    basename=string    [suffix=string]     [nprocs=integer]     [--overwrite]
       [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -n
           Register Null maps

       -r
           Ignore the current region settings and use the raster map regions

       --overwrite
           Allow output files to overwrite existing files

       --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

       output=name [required]
           Name of the output 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’

       size=integer
           Neighborhood size
           Default: 3

       method=string [required]
           Aggregate operation to be performed on the raster maps
           Options: average, median, mode, minimum, maximum, range, stddev, sum, count, variance,
           diversity, interspersion, quart1, quart3, perc90, quantile
           Default: average

       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 r.neighbor processes to run in parallel
           Default: 1

DESCRIPTION

       t.rast.neighbors performs r.neighbors computations on the maps  of  a  space  time  raster
       dataset  (STRDS).  This  module  supports  a  subset  of  options  that  are  available in
       r.neighbors. The size of the neighborhood and the aggregation method can be chosen.

       The user must provide an input and an output space time raster dataset and the basename of
       the  resulting  raster maps. The resulting STRDS will have the same temporal resolution as
       the input dataset.  All maps will be processed using the current region settings.

       The user can select a subset of the input space time raster dataset for processing using a
       SQL  WHERE  statement.  The  number  of  CPU’s  to  be used for parallel processing can be
       specified with the nprocs option to speedup the computation on multi-core system.

EXAMPLE

       To smooth the maps contained in a space time dataset run:
       t.rast.neighbors input=tempmean_monthly output=smooth_tempmean_monthly \
                        basename=tmean_smooth size=5 method=average nprocs=4
       # show some info about the new space time dataset
       t.info smooth_tempmean_monthly
        +-------------------- Space Time Raster Dataset -----------------------------+
        |                                                                            |
        +-------------------- Basic information -------------------------------------+
        | Id: ........................ smooth_tempmean_monthly@climate_2000_2012
        | Name: ...................... smooth_tempmean_monthly
        | Mapset: .................... climate_2000_2012
        | Creator: ................... lucadelu
        | Temporal type: ............. absolute
        | Creation time: ............. 2014-11-27 11:41:36.444579
        | Modification time:.......... 2014-11-27 11:41:39.978232
        | Semantic type:.............. mean
        +-------------------- Absolute time -----------------------------------------+
        | Start time:................. 2009-01-01 00:00:00
        | End time:................... 2013-01-01 00:00:00
        | Granularity:................ 1 month
        | Temporal type of maps:...... interval
        +-------------------- Spatial extent ----------------------------------------+
        | North:...................... 320000.0
        | South:...................... 10000.0
        | East:.. .................... 935000.0
        | West:....................... 120000.0
        | Top:........................ 0.0
        | Bottom:..................... 0.0
        +-------------------- Metadata information ----------------------------------+
        | Raster register table:...... raster_map_register_ea1c9a83524e41a784d72744b08c6107
        | North-South resolution min:. 500.0
        | North-South resolution max:. 500.0
        | East-west resolution min:... 500.0
        | East-west resolution max:... 500.0
        | Minimum value min:.......... -6.428905
        | Minimum value max:.......... 18.867296
        | Maximum value min:.......... 4.247691
        | Maximum value max:.......... 28.767953
        | Aggregation type:........... None
        | Number of registered maps:.. 48
        |
        | Title:
        | Monthly precipitation
        | Description:
        | Dataset with monthly precipitation
        | Command history:
        | # 2014-11-27 11:41:36
        | t.rast.neighbors input="tempmean_monthly"
        |     output="smooth_tempmean_monthly" basename="tmean_smooth" size="5"
        |     method="average" nprocs="4"
        |
        +----------------------------------------------------------------------------+
       # now compare the values between the original and the smoothed dataset
       t.rast.list input=smooth_tempmean_monthly columns=name,start_time,min,max
       name|start_time|min|max
       tmean_smooth_1|2009-01-01 00:00:00|-3.361714|7.409861
       tmean_smooth_2|2009-02-01 00:00:00|-1.820261|7.986794
       tmean_smooth_3|2009-03-01 00:00:00|2.912971|11.799684
       ...
       tmean_smooth_46|2012-10-01 00:00:00|9.38767|18.709297
       tmean_smooth_47|2012-11-01 00:00:00|1.785653|10.911189
       tmean_smooth_48|2012-12-01 00:00:00|1.784212|11.983857
       t.rast.list input=tempmean_monthly columns=name,start_time,min,max
       name|start_time|min|max
       2009_01_tempmean|2009-01-01 00:00:00|-3.380823|7.426054
       2009_02_tempmean|2009-02-01 00:00:00|-1.820261|8.006386
       2009_03_tempmean|2009-03-01 00:00:00|2.656992|11.819274
       ...
       2012_10_tempmean|2012-10-01 00:00:00|9.070884|18.709297
       2012_11_tempmean|2012-11-01 00:00:00|1.785653|10.911189
       2012_12_tempmean|2012-12-01 00:00:00|1.761019|11.983857

SEE ALSO

        r.neighbors, t.rast.aggregate.ds, t.rast.extract, t.info, g.region, r.mask

AUTHOR

       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

       Last changed: $Date: 2016-10-27 23:20:55 +0200 (Thu, 27 Oct 2016) $

SOURCE CODE

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

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