This function samples background points from a raster given a set of presences. The locations returned as the center points of the sampled cells, which can overlap with the presences (in contrast to pseudo-absences, see sample_pseudoabs). The following methods are implemented:
'random': background randomly sampled from the region covered by the raster (i.e. not NAs).
'dist_max': background randomly sampled from the unioned buffers of 'dist_max' from presences (distances in 'm' for lonlat rasters, and in map units for projected rasters). Using the union of buffers means that areas that are in multiple buffers are not oversampled. This is also referred to as "thickening".
'bias': background points are sampled according to a surface representing the biased sampling effort.
Usage
sample_background(
data,
raster,
n,
coords = NULL,
method = "random",
class_label = "background",
return_pres = TRUE
)Arguments
- data
An
sf::sfdata frame, or a data frame with coordinate variables. These can be defined incoords, unless they have standard names (see details below).- raster
the terra::SpatRaster or
starsfrom which cells will be sampled (the first layer will be used to determine which cells are NAs, and thus can not be sampled). If sampling is "bias", then the sampling probability will be proportional to the values on the first layer (i.e. band) of the raster.- n
number of background points to sample.
- coords
a vector of length two giving the names of the "x" and "y" coordinates, as found in
data. If left to NULL, the function will try to guess the columns based on standard namesc("x", "y"),c("X","Y"),c("longitude", "latitude"), orc("lon", "lat").- method
sampling method. One of 'random', 'dist_max', and 'bias'. For dist_max, the maximum distance is set as an additional element of a vector, e.g c('dist_max',70000).
- class_label
the label given to the sampled points. Defaults to
background- return_pres
return presences together with background in a single tibble.
Value
An object of class tibble::tibble. If presences are returned, the
presence level is set as the reference (to match the expectations in the
yardstick package that considers the first level to be the event).