spatialEco (version 2.0-1)

sf.kde: Spatial kernel density estimate

Description

A weighted or unweighted Gaussian Kernel Density estimate for point spatial data

Usage

sf.kde(
  x,
  y = NULL,
  bw = NULL,
  ref = NULL,
  res = NULL,
  standardize = FALSE,
  scale.factor = NULL,
  mask = FALSE
)

Value

a terra SpatRaster class object containing kernel density estimate

Arguments

x

sf POINT object

y

Optional values, associated with x coordinates, to be used as weights

bw

Distance bandwidth of Gaussian Kernel, must be units of projection

ref

A terra SpatRaster, sf class object or c[xmin,xmax,ymin,ymax] vector to estimate the kde extent

res

Resolution of raster when ref not SpatRaster

standardize

Standardize results to 0-1 (FALSE/TRUE)

scale.factor

Optional numeric scaling factor for the KDE (eg., 10000), to account for very small estimate values

mask

(TRUE/FALSE) mask resulting raster if ref is provided as a SpatRaster

Author

Jeffrey S. Evans <[e-mail]>

Details

The automatic bandwidth selection for unweighted KDE uses the Wand & Jones (1994) univariate plug-in whereas, weighted KDE's use the Duong & Hazelton (2005) smoothed cross-validation for creating a diagonal bandwidth matrix.

References

Duong, T. & Hazelton, M.L. (2005) Cross-validation bandwidth matrices for multivariate kernel density estimation. Scandinavian Journal of Statistics, 32, 485-506.

Wand, M.P. & Jones, M.C. (1994) Multivariate plug-in bandwidth selection. Computational Statistics, 9, 97-116.

Examples

# \donttest{ 
library(sf) 
library(terra) 
  
data(meuse, package = "sp")
meuse <- st_as_sf(meuse, coords = c("x", "y"), crs = 28992, 
                  agr = "constant") 
  			
# Unweighted KDE (spatial locations only)				
pt.kde <- sf.kde(x = meuse, bw = 1000, standardize = TRUE, 
                 scale.factor = 10000, res=40)
  plot(pt.kde, main="Unweighted kde")
    plot(st_geometry(meuse), pch=20, col="red", add=TRUE) 

# Weighted KDE using cadmium and extent with automatic bandwidth selection
( e <- st_bbox(meuse)[c(1,3,2,4)] ) 
cadmium.kde <- sf.kde(x = meuse, y = meuse$cadmium, ref = e,  
                      standardize = TRUE, 
					  scale.factor = 10000, res=40)
plot(cadmium.kde)
  plot(st_geometry(meuse), pch=20, col="red", add=TRUE)
 			
# }