v.sample.1grass man page

v.sample — Samples a raster map at vector point locations.


vector, sampling, raster


v.sample --help
v.sample input=name [layer=string] column=name output=name raster=name [method=string] [zscale=float] [--overwrite] [--help] [--verbose] [--quiet] [--ui]


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 point 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.
Default: 1
column=name [required]
Name of attribute column to use for comparison
output=name [required]
Name for output vector map to store differences
raster=name [required]
Name of raster map to be sampled
Sampling interpolation method
Options: nearest, bilinear, bicubic
Default: nearest
nearest: Nearest-neighbor interpolation
bilinear: Bilinear interpolation
bicubic: Bicubic interpolation
Scaling factor for values read from raster map
Sampled values will be multiplied by this factor
Default: 1.0


v.sample samples a GRASS raster map at the point locations in the input file by either cubic convolution interpolation, bilinear interpolation, or nearest neighbor sampling (default).

This program may be especially useful when sampling for cross validation of interpolations whose output is a raster map.


The output points will have the easting and northing of the input points. The input category value is used. The input attribute, raster value and difference is written to output.

When NULL values are encountered for a cell, zero value is used instead. In these cases, more acurrate results may be obtained by using the default nearest neighbor comparisons.

This program may not work properly with lat-long data when the -bc flags are used.

When interpolation is done (i.e., the -bc flags are used), values are assumed to be located at the centroid of grid cells. Therefore, current resolution settings are important.


Comparison of "elev_ned_30m" and "elev_srtm_30m" North Carolina sample dataset elevation models at random positions:

# set computational region:
 g.region raster=elev_srtm_30m -p
# generate random points:
 v.random output=random n=100
# add table with one column:
 v.db.addtable random col="elev_srtm30 double precision"
# transfer elevations at random points into table:
 v.what.rast map=random rast=elev_srtm_30m col=elev_srtm30
# verify:
 v.db.select random
# perform sampling on other elevation map:
 v.sample in=random col=elev_srtm30 rast=elev_ned_30m out=elev_samples
 v.db.select elev_samples
#univariate statistics of differences between elevation maps:
 v.univar elev_samples column=diff type=point

See Also

g.region, v.random, v.what.rast Image Sampling Methods - GRASS Tutorial on s.sample (available as s.sample-tutorial.ps.gz)


James Darrell McCauley
when he was at: Agricultural Engineering Purdue University

Updated for GRASS 5.0 by Eric G. Miller
Updated for GRASS 5.7 by Radim Blazek

Last changed: $Date: 2014-12-19 22:55:37 +0100 (Fri, 19 Dec 2014) $

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