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### r.random.cells: Generates random cell values with spatial dependence.

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## NAME

r.random.cells- Generates random cell values with spatial dependence.## KEYWORDS

raster, random, cell## SYNOPSIS

r.random.cells r.random.cells help r.random.cells output=name distance=float[seed=integer] [--overwrite] [--verbose] [--quiet]Flags: --overwriteAllow output files to overwrite existing files--verboseVerbose module output--quietQuiet module outputParameters: output=nameName for output raster mapdistance=floatMaximum distance of spatial correlation (value(s) >= 0.0)seed=integerRandom seed (SEED_MIN >= value >= SEED_MAX) (default [random])DESCRIPTION

r.random.cellsgenerates a random sets of cells that are at leastdistanceapart. The cells are numbered from 1 to the numbers of cells generated. Random cells will not be generated in areas masked off.Parameters outputRandom 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 radiusdistance.distanceDetermines the minimum distance the centers of the random cells will be apart.seedSpecifies the random seed thatr.random.cellswill use to generate the cells. If the random seed is not given,r.random.cellswill get a seed from the process ID number.## NOTES

The original purpose for this program was to generate independent random samples of cells in a study area. Thedistancevalue is the amount of spatial autocorrelation for the map being studied.## REFERENCES

Random Field Software for GRASS 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: Visualizing Spatial Data Uncertainty Using Animation (final draft), by Charles R. Ehlschlaeger, Ashton M. Shortridge, and Michael F. Goodchild. Submitted to Computers in GeoSciences in September, 1996, accepted October, 1996 for publication in June, 1997. 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.## SEE ALSO

r.random.surface, r.random## AUTHOR

Charles Ehlschlaeger; National Center for Geographic Information and Analysis, University of California, Santa Barbara. Last changed: $Date: 2010-09-21 15:08:34 +0200 (Tue, 21 Sep 2010) $ Full index (C) 2003-2010 GRASS Development Team R.RANDOM.CELLS(1)

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