sample_pseudoabs {tidysdm} | R Documentation |
Sample pseudo-absence (or background) points for SDM analysis
Description
This function samples pseudo-absence (or background, the naming is a matter of semantics) points from a raster given a set of presences. The locations returned as the center points of the sampled cells, which can not overlap with the presences. The following methods are implemented:
'random': pseudo-absences/background randomly sampled from the region covered by the raster (i.e. not NAs).
'dist_min': pseudo-absences/background randomly sampled from the region excluding a buffer of 'dist_min' from presences (distances in 'm' for lonlat rasters, and in map units for projected rasters).
'dist_max': pseudo-absences/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".
'dist_disc': pseudo-absences/background randomly sampled from the unioned discs around presences with the two values of 'dist_disc' defining the minimum and maximum distance from presences.
Usage
sample_pseudoabs(
data,
raster,
n,
coords = NULL,
method = "random",
class_label = "pseudoabs",
return_pres = TRUE
)
Arguments
data |
An |
raster |
the terra::SpatRaster from which cells will be sampled |
n |
number of pseudoabsence/background points to sample |
coords |
a vector of length two giving the names of the "x" and "y"
coordinates, as found in |
method |
sampling method. One of 'random', 'dist_min', 'dist_max', or 'dist_disc'. Threshold distances are set as additional elements of a vector, e.g c('dist_min',70000) or c('dist_disc',50000,200000). |
class_label |
the label given to the sampled points. Defaults to |
return_pres |
return presences together with pseudoabsences/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)