idw.smoothing {spatialEco} | R Documentation |
Inverse Distance Weighted smoothing
Description
Distance weighted smoothing of a variable in a spatial point object
Usage
idw.smoothing(x, y, d, k)
Arguments
x |
An sf POINT class object |
y |
Numeric data column in x to be smoothed |
d |
Distance constraint |
k |
Maximum number of k-nearest neighbors within d |
Details
Smoothing is conducted with a weighted-mean where; weights represent inverse standardized distance lags Distance-based or neighbour-based smoothing can be specified by setting the desired neighbour smoothing method to a specified value then the other parameter to the potential maximum. For example; a constraint distance, including all neighbors within 1000 (d=1000) would require k to equal all of the potential neighbors (n-1 or k=nrow(x)-1).
Value
A vector, same length as nrow(x), of smoothed y values
Examples
library(sf)
if(require(sp, quietly = TRUE)) {
data(meuse, package = "sp")
meuse <- st_as_sf(meuse, coords = c("x", "y"), crs = 28992,
agr = "constant")
# Calculate distance weighted mean on cadmium variable in meuse data
cadmium.idw <- idw.smoothing(meuse, 'cadmium', k=nrow(meuse), d = 1000)
meuse$cadmium.wm <- cadmium.idw
opar <- par(no.readonly=TRUE)
par(mfrow=c(2,1))
plot(density(meuse$cadmium), main='Cadmium')
plot(density(meuse$cadmium.wm), main='IDW Cadmium')
par(opar)
plot(meuse[c("cadmium","cadmium.wm")], pch=20)
} else {
cat("Please install sp package to run example", "\n")
}
[Package spatialEco version 2.0-2 Index]