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NAME

r.sample.category - Create sampling points from each category in a raster map

KEYWORDS

raster, sampling, random, points, vector, stratified sampling

SYNOPSIS

r.sample.category
r.sample.category --help
r.sample.category [-s] input=name output=name [sampled=name[,name,...]] npoints=integer[,integer,...] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-s
If number of cells in category < npoints, skip category
--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 raster map with categories (classes)
output=name [required]
Name of output vector map with points at random locations
sampled=name[,name,...]
Names of input raster maps to be sampled
npoints=integer[,integer,...] [required]
Number of sampling points per category in the input map
You can provide multiple numbers, one for each category in input raster (sorted ascending)

Table of contents

DESCRIPTION

r.sample.category generates points at random locations. Each category (class) in a raster map will contain specified number of random points.

Different number of points can be specified for different categories. For example, if there are categories 1, 4, 7 in the input raster map, and npoints=100,200,300, 100 points will be generated in category 1, 200 points in category 4 and 300 points in category 7. If only one number is specified, it will be used for every category.

NOTES

Mask (r.mask) to create points in areas with each category, thus mask cannot be active when the module is used.

Categories are identified based on current computational region.

EXAMPLE

Generate random points

Generate three points at random location for each category (class) in the raster map:
g.region raster=landclass96
r.sample.category input=landclass96 output=landclass_points npoints=3
Show the result:
d.rast map=landclass96
d.vect map=landclass_points icon=basic/circle fill_color=aqua color=blue size=10


Figure: Three random points in each category of landclass raster map

Create a table with values sampled from rasters

Create 2 random points per each category (class) in landclass96 raster and sample elevation and geology_30m rasters at these points:
r.sample.category input=landclass96 output=landclass_points sampled=elevation,geology_30m npoints=2
Look at the created data:
v.db.select landclass_points sep=comma
The result of v.db.select is CSV table which can be used, for example in a spreadsheet application:
cat,landclass96,elevation,geology_30m
1,1,102.7855,270
2,1,105.78,270
3,2,114.5954,217
4,2,137.4816,921
5,3,71.19167,270
6,3,93.33904,270
7,4,76.41077,262
8,4,97.54424,217
9,5,138.455,405
10,5,88.8075,270
11,6,126.5298,217
12,6,86.73177,217
13,7,134.5381,217
14,7,99.6844,270

KNOWN ISSUES

The module does not respect mask. More precisely it does not allow mask to be active when it is started because it sets the mask by itself for its own purposes. The mask is removed at the end of execution but all other modules executed in parallel with this module (such as rendering maps in GUI) will be influenced by the mask set by this module.

SEE ALSO

v.sample, r.random, r.random.cells, v.random, v.what.rast, r.describe

AUTHORS

Vaclav Petras, NCSU OSGeoREL,
Anna Petrasova, NCSU OSGeoREL

Last changed: $Date: 2015-06-12 05:31:56 +0200 (Fri, 12 Jun 2015) $

SOURCE CODE

Available at: r.sample.category source code (history)


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