uniformSampling performs the uniform sampling of observations within the environmental space. Note that uniformSampling can be more generally used to sample observations (not necessarily associated with species occurrence data) within bi-dimensional spaces (e.g., vegetation plots). Being designed with species distribution models in mind, uniformSampling allows collectively sampling observations for both the training and testing dataset (optional).
In both cases, the user must provide a number of observations that will be sampled in each cell of the sampling grid (n.tr: points for the training dataset; n.ts: points for the testing dataset). Note that the optimal resolution of the sampling grid can be found using the optimRes function.
Usage
uniformSampling(
sdf,
grid.res,
n.tr = 5,
n.prev = NULL,
sub.ts = FALSE,
n.ts = 5,
plot_proc = FALSE,
verbose = FALSE
)Arguments
- sdf
an sf object having point geometry given by the PC-scores values
- grid.res
(integer) resolution of the sampling grid. The resolution can be arbitrarily selected or defined using the
optimRes()function.- n.tr
(integer; optional) number of expected points given a certain prevalence threshold for the training dataset.
- n.prev
(double) sample prevalence
- sub.ts
(logical) sample the validation points
- n.ts
(integer; optional) number of points for the testing dataset to sample in each cell of the sampling grid. sub.ts argument must be TRUE.
- plot_proc
(logical) plot progress of the sampling
- verbose
(logical) Print verbose