Background sample

Creates a point sample that can be used as a NULL for SDM's and other modeling approaches.

background(
  x,
  ext = NULL,
  p = 1000,
  known = NULL,
  d = NULL,
  type = c("regular", "random", "hexagon", "nonaligned")
)

Arguments

x	A polygon defining sample region
ext	Vector of extent coordinates (xmin, xmax, ymin, ymax)
p	Size of sample
known	SpatialPoints of known locations (same CSR as x)
d	Threshold distance for known proximity
type	Type of sample c("systematic", "random", "hexagon", "nonaligned")

Value

A SpatialPointsDataFrame or data.frame with x,y coordinates

Note

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.

Author

Jeffrey S. Evans <jeffrey_evans@tnc.org>

Examples

library(sp)
library(raster)
#> 
#> Attaching package: 'raster'
#> The following object is masked from 'package:spatialEco':
#> 
#>     shift
library(rgeos)
#> rgeos version: 0.5-5, (SVN revision 640)
#>  GEOS runtime version: 3.8.0-CAPI-1.13.1 
#>  Linking to sp version: 1.4-5 
#>  Polygon checking: TRUE 
  data(meuse)
  coordinates(meuse) <- ~x+y

# create "known" locations  
locs <- meuse[sample(1:nrow(meuse), 5),]

# systematic sample using extent polygon
e <- as(extent(meuse), "SpatialPolygons")
s <- background(e, p=1000, known=locs, d=300)
  plot(s,pch=20)
    points(locs, pch=20, col="red")

# systematic sample using irregular polygon
data(meuse.grid)
  coordinates(meuse.grid) = c("x", "y")
  gridded(meuse.grid) = TRUE
meuse.poly = gUnaryUnion(as(meuse.grid, "SpatialPolygons"))

s <- background(meuse.poly, p=1000, known=locs, d=200)
  plot(s,pch=20)
    plot(meuse.poly, add=TRUE)
    points(locs, pch=20, col="red")

# random sample using irregular polygon
s <- background(meuse.poly, p=500, known=locs, 
                d=200, type="random")
  plot(s,pch=20)
    plot(meuse.poly, add=TRUE)
    points(locs, pch=20, col="red")

# systematic sample using defined extent
extent(meuse)
#> class      : Extent 
#> xmin       : 178605 
#> xmax       : 181390 
#> ymin       : 329714 
#> ymax       : 333611 
s <- background(ext=c(178605, 181390, 329714, 333611), 
                p=1000, known=locs, d=300)
  plot(s,pch=20)
    points(locs, pch=20, col="red")