Proximity Index
Calculates proximity index for a set of polygons
proximity.index(x, y = NULL, min.dist = 0, max.dist = 1000, background = NULL)
x |
A polygon class sp or sf object |
y |
Optional column in data containing classes |
min.dist |
Minimum threshold distance |
max.dist |
Maximum neighbor distance |
background |
Optional value in y column indicating background value |
A vector equal to nrow(x) of proximity index values, if a background value is specified NA values will be returned in the position(s) of the specified class
Jeffrey S. Evans <jeffrey_evans@tnc.org>
Gustafson, E.J., & G.R. Parker (1994) Using an Index of Habitat Patch Proximity for Landscape Design. Landscape and Urban Planning 29:117-130
library(sp)
library(rgeos)
# Create test polygons
data(meuse)
coordinates(meuse) = ~x+y
meuse_poly <- gBuffer(meuse, width = meuse$elev * 5, byid = TRUE)
meuse_poly$LU <- sample(c("forest","nonforest"), nrow(meuse_poly),
replace=TRUE)
# All polygon proximity index 1000 radius
( pidx <-proximity.index(meuse_poly, min.dist = 1) )
pidx[pidx > 100] <- 100
# Class-level proximity index 1000 radius
( pidx.class <- proximity.index(meuse_poly, y = "LU", min.dist = 1) )
pidx.class[pidx.class > 100] <- 100
# plot index for all polygons
meuse_poly$pidx <- pidx
spplot(meuse_poly, "pidx")
# plot index for class-level polygons
meuse_poly$cpidx <- pidx.class
spplot(meuse_poly, "cpidx")
# plot index for just forest class
forest <- meuse_poly[meuse_poly$LU == "forest",]
spplot(forest, "cpidx")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.