dismo (version 1.3-16)

Convex Hull: Convex hull model

Description

The Convex hull model predicts that a species is present at sites inside the convex hull of a set of training points, and absent outside that hull. I.e. this is the spatial convex hull, not an environmental hull.

Usage

convHull(x, ...)

Value

An object of class 'ConvexHull' (inherits from DistModel-class)

Arguments

x

point locations (presence). Two column matrix, data.frame or SpatialPoints* object

...

Additional arguments. See details

Author

Robert J. Hijmans

Details

You can supply an argument n (>= 1) to get n convex hulls around subsets of the points. You can also set n=1:x, to get a set of overlapping polygons consisting of 1 to x parts. I.e. the first polygon has 1 part, the second has 2 parts, and x has x parts.

See Also

predict, geoDist, maxent, domain, mahal

Examples

r <- raster(system.file("external/rlogo.grd", package="raster"))
#presence data
pts <- matrix(c(17, 42, 85, 70, 19, 53, 26, 84, 84, 46, 48, 85, 4, 95, 48, 54, 66, 
 74, 50, 48, 28, 73, 38, 56, 43, 29, 63, 22, 46, 45, 7, 60, 46, 34, 14, 51, 70, 31, 39, 26), ncol=2)
train <- pts[1:12, ]
test <- pts[13:20, ]
				 
ch <- convHull(train)
predict(ch, test)

plot(r)
plot(ch, border='red', lwd=2, add=TRUE)
points(train, col='red', pch=20, cex=2)
points(test, col='black', pch=20, cex=2)

pr <- predict(ch, r, progress='')
plot(pr)
points(test, col='black', pch=20, cex=2)
points(train, col='red', pch=20, cex=2)

# to get the polygons:
p <- polygons(ch)
p