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A CAR landscape simulator for isotropic conditions.
CARsimu(LEVEL = 6, rho = 0.2499, row2 = 0, col2 = 0, rc1 = 0, cr1 = 0,
maindi = 1, rajz = TRUE)The output is a simulated map on a grid (provided as a matrix).
This is the power (n) with base 2 that defines the image size: 2^n x 2^n.
This is the spatial autocorrelation parameter.
For later implementation - 2nd order neighbour spatial autocorrelation parameter (rows).
For later implementarion - 2nd order neighbour spatial autocorrelation parameter (columns).
For later implementation - diagonal spatial autocorreltion parameter.
For later implementation - diagonal spatial autocorrelation parameter.
For later implementation.
When rajz = TRUE, the simulated map will be drawn.
Ferenc (Ferko) Csillag and Sandor Kabos; modified by Tarmo K. Remmel
This function can actually be parameterized in many ways, however, for isotropic landscapes, only the rho parameter is to be used. Additional parameterizations, although possible, are not permitted with the use of the other functions provided with the PatternClass package
Remmel, T.K. and F. Csillag. 2003. When are two landscape pattern indices significantly different? Journal of Geographical Systems 5(4):331-351.
Remmel, T.K. and M.-J. Fortin. 2013. Categorical class map patterns: characterization and comparison. Landscape Ecology. DOI: 10.1007/s/10980-013-9905-x.
Remmel, T.K. and M.-J. Fortin. What constitutes a significant difference in landscape pattern? (using R) (Pending 2014). In Gergel, S.E. and M.G. Turner. Learning landscape ecology: concepts and techniques for a sustainable world (2nd ed.). New York: Springer.
See Also as singlemap
CARsimu(LEVEL = 6, rho = 0.2499, row2 = 0, col2 = 0, rc1 = 0, cr1 = 0,
maindi = 1, rajz = TRUE)
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