Note: A new GRASS GIS stable version has been released: GRASS GIS 7.4, available here.
Updated manual page: here
NAME
r.random.cells - Generates random cell values with spatial dependence.
KEYWORDS
raster,
sampling,
random,
autocorrelation
SYNOPSIS
r.random.cells
r.random.cells --help
r.random.cells output=name distance=float [seed=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
- --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:
- output=name [required]
- Name for output raster map
- distance=float [required]
- Maximum distance of spatial correlation (value >= 0.0)
- seed=integer
- Random seed (SEED_MIN >= value >= SEED_MAX) (default [random])
r.random.cells generates a random sets of raster cells that are
at least
distance apart. The cells are numbered from 1 to the
numbers of cells generated, all other cells are 0 (zero). Random
cells will not be generated in areas masked off.
- output
- Random cells. Each random cell has a unique non-zero cell value
ranging from 1 to the number of cells generated. The heuristic for
this algorithm is to randomly pick cells until there are no cells
outside of the chosen cell's buffer of radius distance.
- distance
- Determines the minimum distance the centers of the random cells
will be apart.
- seed
- Specifies the random seed that
r.random.cells will use to generate the cells. If the random seed
is not given, r.random.cells will get a seed from the process ID
number.
The original purpose for this program was to generate independent
random samples of cells in a study area. The
distance value is
the amount of spatial autocorrelation for the map being studied.
North Carolina sample dataset example:
g.region n=228500 s=215000 w=630000 e=645000 res=100 -p
r.random.cells output=random_500m distance=500
# optionally set 0 to NULL (masked off areas)
r.null random_500m setnull=0
Random Field Software for GRASS GIS by Chuck Ehlschlaeger
As part of my dissertation, I put together several programs that help
GRASS (4.1 and beyond) develop uncertainty models of spatial data. I hope
you find it useful and dependable. The following papers might clarify their
use:
- Ehlschlaeger, C.R., Shortridge, A.M., Goodchild, M.F., 1997.
Visualizing spatial data uncertainty using animation.
Computers & Geosciences 23, 387-395. doi:10.1016/S0098-3004(97)00005-8
- Modeling
Uncertainty in Elevation Data for Geographical Analysis, by
Charles R. Ehlschlaeger, and Ashton M. Shortridge. Proceedings of the
7th International Symposium on Spatial Data Handling, Delft,
Netherlands, August 1996.
- Dealing
with Uncertainty in Categorical Coverage Maps: Defining, Visualizing,
and Managing Data Errors, by Charles Ehlschlaeger and Michael
Goodchild. Proceedings, Workshop on Geographic Information Systems at
the Conference on Information and Knowledge Management, Gaithersburg
MD, 1994.
- Uncertainty
in Spatial Data: Defining, Visualizing, and Managing Data
Errors, by Charles Ehlschlaeger and Michael
Goodchild. Proceedings, GIS/LIS'94, pp. 246-253, Phoenix AZ,
1994.
r.random.surface,
r.random
Charles Ehlschlaeger; National Center for Geographic Information and
Analysis, University of California, Santa Barbara.
Last changed: $Date: 2015-04-21 07:00:05 -0700 (Tue, 21 Apr 2015) $
SOURCE CODE
Available at: r.random.cells source code (history)
Note: A new GRASS GIS stable version has been released: GRASS GIS 7.4, available here.
Updated manual page: here
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GRASS Development Team,
GRASS GIS 7.0.7svn Reference Manual