xenial (1) t.rast.neighbors.1grass.gz

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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   [-n]   input=name   output=name    [where=sql_query]    [size=integer]   method=string
       basename=string  [nprocs=integer]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -n
           Register Null maps

       --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

       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 into 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 original data and the smoothed one
       t.rast.list input=smooth_tempmean_monthly columns=name,start_time,min,max
       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: 2016-01-13 00:30:14 +0100 (Wed, 13 Jan 2016) $

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