Sample background points for SDM analysis for points with a time point.

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_time). The following methods are implemented:

'random': background points randomly sampled from the region covered by the raster (i.e. not NAs).
'dist_max': background points 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. Note that the surface for each time step is normalised to sum to 1;use n_per_time_step to affect sampling effort within each time step.

Usage

sample_background_time(
  data,
  raster,
  n_per_time_step,
  coords = NULL,
  time_col = "time",
  lubridate_fun = c,
  method = "random",
  class_label = "background",
  return_pres = TRUE,
  time_buffer = 0
)

Arguments

data: An sf::sf data frame, or a data frame with coordinate variables. These can be defined in coords, unless they have standard names (see details below).
raster: the terra::SpatRaster or terra::SpatRasterDataset from which cells will be sampled. If a terra::SpatRasterDataset, the first dataset will be used to define which cells are valid, and which are NAs.
n_per_time_step: number of background points to sample for each time step (i.e. a vector of length equal to the number of time steps in raster)
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 names c("x", "y"), c("X","Y"), c("longitude", "latitude"), or c("lon", "lat")
time_col: The name of the column with time; if time is not a lubridate object, use lubridate_fun to provide a function that can be used to convert appropriately
lubridate_fun: function to convert the time column into a lubridate object
method: sampling method. One of 'random', 'dist_min', 'dist_max', or 'dist_disc'.
class_label: the label given to the sampled points. Defaults to background
return_pres: return presences together with background in a single tibble
time_buffer: the buffer on the time axis around presences that defines their effect when sampling background with method 'max_dist'. If set to zero, presences have an effect only on the time step to which they are assigned in raster; if a positive value, it defines the number of days before and after the date provided in the time column for which the presence should be considered (e.g. 20 days means that a presence is considered in all time steps equivalent to plus and minus twenty days from its date).

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)