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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 v.extract --help v.extract [-dtr] input=name [layer=string] [type=string[,string,...]] [cats=range] [where=sql_query] output=name [file=name] [random=integer] [new=integer] [dissolve_column=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui] Flags: -d Dissolve common boundaries (default is no) -t Do not copy attributes (see also ’new’ parameter) -r Reverse selection --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 input vector map Or data source for direct OGR access layer=string Layer number or name (’-1’ for all layers) A single vector map can be connected to multiple database tables. This number determines which table to use. When used with direct OGR access this is the layer name. Default: 1 type=string[,string,...] Types to be extracted Input feature type Options: point, line, boundary, centroid, area, face Default: point,line,boundary,centroid,area,face cats=range Category values Example: 1,3,7-9,13 where=sql_query WHERE conditions of SQL statement without ’where’ keyword Example: income < 1000 and population >= 10000 output=name [required] Name for output vector map file=name Input text file with category numbers/number ranges to be extracted If ’-’ given reads from standard input random=integer Number of random categories matching vector objects to extract Number must be smaller than unique cat count in layer new=integer Desired new category value (enter -1 to keep original categories) If new >= 0, attributes is not copied Default: -1 dissolve_column=name Name of attribute column for dissolving areas Preserves category values
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 in the selected layer 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, or use layer=-1.
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: 2018-05-04 16:47:55 +0200 (Fri, 04 May 2018) $
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