v.extract.1grass man page
v.extract — Selects vector features from an existing vector map and creates a new vector map containing only the selected features.
vector, extract, select, dissolve, random
v.extract [-dtr] input=name [layer=string] [type=string[,string,...]] [cats=range] [where=sql_query] output=name [file=name] [random=integer] [new=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Dissolve common boundaries (default is no)
Do not copy attributes (see also ’new’ parameter)
Allow output files to overwrite existing files
Print usage summary
Verbose module output
Quiet module output
Force launching GUI dialog
- input=name [required]
Name of input vector map
Or data source for direct OGR access
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.
Types to be extracted
Input feature type
Options: point, line, boundary, centroid, area, face
WHERE conditions of SQL statement without ’where’ keyword
Example: income < 1000 and population >= 10000
- output=name [required]
Name for output vector map
Input text file with category numbers/number ranges to be extracted
If ’-’ given reads from standard input
Number of random categories matching vector objects to extract
Number must be smaller than unique cat count in layer
Desired new category value (enter -1 to keep original categories)
If new >= 0, attributes is not copied
v.extract allows a user to select vector objects from an existing vector map and creates a new map containing only the selected objects. Database tables can be queried with SQL statements, if a connection is established. Dissolving (optional) is based on the output categories. If 2 adjacent areas have the same output category, the boundary is removed.
If cats, file, random or where options are not specified, all features of given type and layer are extracted. Categories are not changed in that case.
Only features with a category number will be extracted. So if you want to extract boundaries (which are usually without category, as that information is normally held in the area’s centroid) you must first use v.category to add them.
The examples are intended for the North Carolina sample dataset:
Extract areas by category number with dissolving #1
v.extract -d cats=1,2,3,4 input=soils_wake output=soil_groupa type=area new=0
produces a new vector soil_groupa, containing those areas from vector soils which have category numbers 1 thru 4; any common boundaries are dissolved, and all areas in the new map will be assigned category number 0.
Extract areas by category number with dissolving #2
v.extract -d cats=1-4 input=soils_wake output=soil_groupa type=area new=-1
produces a new vector map soil_groupa containing the areas from vector soils which have categories 1 thru 4. Any common boundaries are dissolved, all areas in the new map will retain their original category numbers 1 thru 4, since new was set to -1.
Extract all areas and assign the same category to all
v.extract input=soils_wake output=soil_groupa type=area new=1
produces a new vector map soil_groupa containing all areas from soils. No common boundaries are dissolved, all areas of the new map will be assigned category number 1.
Extract vectors with SQL
v.extract input=markveggy.shp output=markveggy.1 new=13 \ where="(VEGTYPE = ’Wi’) or (VEGTYPE = ’PS’) or (PRIME_TYPE=’Wi’)"
produces a new vector map with category number 13 if the SQL statement is fulfilled.
Extract vector features which have the given field empty
v.extract input=lakes output=lakes_gaps where="FTYPE is NULL"
Extract vector features which have the given field not empty
v.extract input=lakes output=lakes_ftype where="FTYPE not NULL"
Reverse extracting (behaves like selective vector objects deleting)
Remove meteorological stations from map which are located above 1000m:
# check what to delete: v.db.select precip_30ynormals where="elev > 1000" # perform reverse selection v.extract -r input=precip_30ynormals output=precip_30ynormals_lowland \ where="elev > 1000" # verify v.db.select precip_30ynormals_lowland
Dissolving based on column attributes
# check column names: v.info -c zipcodes_wake # reclass based on desired column: v.reclass input=zipcodes_wake output=zipcodes_wake_recl_nam column=ZIPNAME # verify: v.info -c zipcodes_wake_recl_nam v.db.select zipcodes_wake_recl_nam # dissolve: v.extract -d input=zipcodes_wake_recl_nam output=zipcodes_wake_regions
This produces a new vector map with common boundaries dissolved where the reclassed attributes of adjacent (left/right) areas are identical.
Extract 3 random areas from geology map
v.extract input=geology output=random_geology type=area random=3
This creates a new map with three random categories matching areas. Note that there may be more than one feature with the same category.
v.category, v.dissolve, v.reclass, GRASS SQL interface
R.L. Glenn, USDA, SCS, NHQ-CGIS
GRASS 6 port by Radim Blazek
Last changed: $Date: 2016-03-16 21:17:59 +0100 (Wed, 16 Mar 2016) $
Available at: v.extract source code (history)
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