NAME

       t.vect.extract  - Extracts a subset of a space time vector dataset.

KEYWORDS

       temporal, extract, vector, time

SYNOPSIS

       t.vect.extract
       t.vect.extract --help
       t.vect.extract  [-n]  input=name   [where=sql_query]   [expression=sql_query]  output=name
       [layer=string]     [type=string[,string,...]]      [basename=string]      [nprocs=integer]
       [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -n
           Register empty 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 vector 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’

       expression=sql_query
           WHERE conditions of SQL statement without ’where’ keyword
           Example: income < 1000 and inhab >= 10000

       output=name [required]
           Name of the output space time vector dataset

       layer=string
           Layer number or name
           Vector features can have category values in different layers. This  number  determines
           which layer to use. When used with direct OGR access this is the layer name.
           Default: 1

       type=string[,string,...]
           Input feature type
           Options: point, line, boundary, centroid, area
           Default: point,line,boundary,centroid,area

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

       nprocs=integer
           The number of v.extract processes to run in parallel. Use only if database backend  is
           used which supports concurrent writing
           Default: 1

DESCRIPTION

       The purpose of t.vect.extract is to extract a subset of a space time vector dataset and to
       store that subset in a different space time vector dataset.

EXAMPLE

       In the following example a new space time vector dataset will be create with all the  data
       later than 2000:
       t.vect.extract input=shoreline where="start_time > 2000" \
                      output=shoreline_later_2000 basename=new_shoreline
       t.info shoreline_later_2000@shoreline type=stvds
        +-------------------- Space Time Vector Dataset -----------------------------+
        |                                                                            |
        +-------------------- Basic information -------------------------------------+
        | Id: ........................ shoreline_later_2000@shoreline
        | Name: ...................... shoreline_later_2000
        | Mapset: .................... shoreline
        | Creator: ................... lucadelu
        | Temporal type: ............. relative
        | Creation time: ............. 2014-11-29 08:43:50.043219
        | Modification time:.......... 2014-11-29 08:43:50.085407
        | Semantic type:.............. mean
        +-------------------- Relative time -----------------------------------------+
        | Start time:................. 2003
        | End time:................... 2009
        | Relative time unit:......... years
        | Granularity:................ 1
        | Temporal type of maps:...... point
        +-------------------- Spatial extent ----------------------------------------+
        | North:...................... 1039175.31479
        | South:...................... 34705.216018
        | East:.. .................... 3052322.44671
        | West:....................... 2130004.16779
        | Top:........................ 0.0
        | Bottom:..................... 0.0
        +-------------------- Metadata information ----------------------------------+
        | Vector register table:...... vector_map_register_8395740fc8de42149fef74a3d25bbb05
        | Number of points ........... 0
        | Number of lines ............ 407
        | Number of boundaries ....... 0
        | Number of centroids ........ 0
        | Number of faces ............ 0
        | Number of kernels .......... 0
        | Number of primitives ....... 407
        | Number of nodes ............ 767
        | Number of areas ............ 0
        | Number of islands .......... 0
        | Number of holes ............ 0
        | Number of volumes .......... 0
        | Number of registered maps:.. 3
        |
        | Title:
        | North Carolina shoreline
        | Description:
        | North Caroline shoreline from 2000 to 2009
        | Command history:
        | # 2014-11-29 08:43:50
        | t.vect.extract input="shoreline"
        |     where="start_time > 2000" output="shoreline_later_2000"
        |     basename="new_shoreline"
        | # 2014-11-29 08:44:14
        | t.support type="stvds"
        |     input="shoreline_later_2000@shoreline"
        |     descr="North Caroline shoreline from 2000 to 2009"
        +----------------------------------------------------------------------------+
       t.vect.list shoreline_later_2000
       name|layer|mapset|start_time|end_time
       shoreline_2003|None|shoreline|2003|None
       shoreline_2004|None|shoreline|2004|None
       shoreline_2009|None|shoreline|2009|None

SEE ALSO

        t.create, t.info

AUTHOR

       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

       Last changed: $Date: 2015-09-22 10:12:20 +0200 (Tue, 22 Sep 2015) $

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