Geographic Distance: Geographic distance model

Description

The geographic distance model predicts that the likelyhood of presence is highest near places where a species has been observed. It can be used as a null-model to calibrate cross-validation scores with.

The predicted values are the inverse distance to the nearest known presence point. Distances smaller than or equal to zero are set to 1 (highest score).

Usage

geoDist(p, ...)

Value

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

Arguments

p: point locations (presence). Two column matrix, data.frame or SpatialPoints* object
...: Additional arguments. You must supply a lonlat= argument (logical), unless p is a SpatialPoints* object and has a valid CRS (coordinate reference system). You can also supply an additional argument 'a' for absence points (currently ignored). Argument 'a' should be of the same class as argument 'p'

Author

Robert J. Hijmans

Examples

Run this code

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)
colnames(pts) <- c('x', 'y')

train <- pts[1:12, ]
test <- pts[13:20, ]
				 
gd <- geoDist(train, lonlat=FALSE)
p <- predict(gd, r)

if (FALSE) {
plot(p)
points(test, col='black', pch=20, cex=2)
points(train, col='red', pch=20, cex=2)
}