Function to extract nearest neighbour predictor values of provided points

This function performs nearest neighbour matching between biodiversity observations and independent predictors, and operates directly on provided data.frames. Note that despite being parallized this function can be rather slow for large data volumes of data!

Usage

get_ngbvalue(
  coords,
  env,
  longlat = TRUE,
  field_space = c("x", "y"),
  cheap = FALSE,
  ...
)

Arguments

coords: A matrix, data.frame or sf object.
env: A data.frame object with the predictors.
longlat: A logical variable indicating whether the projection is long-lat.
field_space: A vector highlight the columns from which coordinates are to be extracted (Default: c('x','y')).
cheap: A logical variable whether the dataset is considered to be large and faster computation could help.
...: other options.

Value

A data.frame with the extracted covariate data from each provided data point.

Details

Nearest neighbour matching is done via the geodist R-package (geodist::geodist).

Note

If multiple values are of equal distance during the nearest neighbour check, then the results is by default averaged.

References

Mark Padgham and Michael D. Sumner (2021). geodist: Fast, Dependency-Free Geodesic Distance Calculations. R package version 0.0.7. https://CRAN.R-project.org/package=geodist

Examples

if (FALSE) {
 # Create matchup table
tab <- get_ngbvalue( coords = coords, # Coordinates
                     env = env # Data.frame with covariates and coordinates
                  )
}