background {spatialEco} | R Documentation |
Background sample
Description
Creates a point sample that can be used as a NULL for SDM's and other modeling approaches.
Usage
background(
x,
p = 1000,
known = NULL,
d = NULL,
type = c("regular", "random", "hexagon", "nonaligned")
)
Arguments
x |
A sf class polygon defining sample region |
p |
Size of sample |
known |
An sf POINT class of known locations with same CSR as x |
d |
Threshold distance for known proximity |
type |
Type of sample c("systematic", "random", "hexagon", "nonaligned") |
Details
This function creates a background point sample based on an extent or polygon sampling region. The known argument can be used with d to remove sample points based on distance-based proximity to existing locations (eg., known species locations). The size (p) of the resulting sample will be dependent on the known locations and the influence of the distance threshold (d). As such, if the know and d arguments are provided the exact value provided in p will not be returned.
Value
A sf POINT feature class or data.frame with x,y coordinates
Author(s)
Jeffrey S. Evans <jeffrey_evans@tnc.org>
Examples
library(sf)
# define study area
sa <- suppressWarnings(st_cast(st_read(
system.file("shape/nc.shp",
package="sf")), "POLYGON"))
sa <- sa[10,]
# create "known" locations
locs <- st_sample(sa, 50)
st_crs(locs) <- st_crs(sa)
# systematic sample using extent polygon
e <- st_as_sf(st_as_sfc(st_bbox(sa)))
st_crs(e) <- st_crs(sa)
s <- background(e, p=1000, known=locs, d=1000)
plot(st_geometry(s), pch=20)
plot(st_geometry(locs), pch=20, col="red", add=TRUE)
# systematic sample using irregular polygon
s <- background(sa, p=1000, known=locs, d=1000)
plot(st_geometry(sa))
plot(st_geometry(s), pch=20, add=TRUE)
plot(st_geometry(locs), pch=20, col="red", add=TRUE)
# random sample using irregular polygon
s <- background(sa, p=500, known=locs,
d=1000, type="random")
plot(st_geometry(sa))
plot(st_geometry(s), pch=20, add=TRUE)
plot(st_geometry(locs), pch=20, col="red", add=TRUE)