spatialEco (version 1.3-7)

proximity.index: Proximity Index

Description

Calculates proximity index for a set of polygons

Usage

proximity.index(x, y = NULL, min.dist = 0, max.dist = 1000, background = NULL)

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

Arguments

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

Author

Jeffrey S. Evans <[e-mail]>

References

Gustafson, E.J., & G.R. Parker (1994) Using an Index of Habitat Patch Proximity for Landscape Design. Landscape and Urban Planning 29:117-130

Examples

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")