surfplot {ShapePattern} | R Documentation |
Produce graphic plots providing class-focused pattern metric context for a landcape map
Description
This function produces three separate plots on a 1 row by 3 column output view. The first plot is the expected mean surface for a selected class-focused pattern metric across the possible range of composition and configuration. A dropped marker can be added to the plot that depicts the position of any combination of composition or configuration parameterization. The second and thrid plots provide series of boxplots representing orthogonal cross-sections of the surface in the first plot, intersecting at the specified location. This provides a sense of how the selected metric's expected value and variability will change as the composition and/or configuration parameter are altered.
Usage
surfplot(metric = 9, prop = 0.7, rho = 0.2, colour = TRUE, drop = TRUE,
cross = TRUE, dat=data$surfaces)
Arguments
metric |
An integer identifying the class-focused pattern metric that the plots will represent. These integers are listed in the source code for |
prop |
A real value between zero (0) and one (1) that defines the proportion of the focal land cover category. This value along with |
rho |
A real value between zero (0) and one (1) that defines the level of spatial autocorrelation for the focal land cover category. This value along with |
colour |
A Boolean indication as to whether the plot should contain colour (TRUE) or not (FALSE). |
drop |
A Boolean indication as to whether the specified point based on composition ( |
cross |
A Boolean indication as to whether the cross-sectional boxplots should be drawn (TRUE) or not (FALSE). |
dat |
A numeric array object created by |
Details
This function requires a valid result from the function buildsurfs
to exist. That result is an array of simulated maps for a series of replicates produced for all pair-wise paramterizations of composition and configuration. This object can be quite large; however, needs to only be produced once. All polts thereafter can be produced (for any class-focused metric) from this stored object. To save processing time, the PatternClass package is provided with these reference (lookup) surfaces already produced for 64x64 images. Future developments will permit these layers to be produced at a wider range of extents.
Value
This function returns a graphic plot.
Note
No further notes at this time.
Author(s)
Tarmo K. Remmel
References
Remmel, T.K. and M.-J. Fortin. What constitutes a significant difference in landscape pattern? (using R). 2016. In Gergel, S.E. and M.G. Turner. Learning landscape ecology: concepts and techniques for a sustainable world (2nd ed.). New York: Springer.
See Also
See Also singlemap
, singleplotter
, buildsurfs
, and doubleplotter
.
Examples
surfplot(metric = 9, prop = 0.7, rho = 0.2, colour = TRUE, drop = TRUE,
cross = TRUE, dat=data$surfaces)