Determine which areas of a sample unit should be prioritized

This function offers two ways to enforce some prioritization within the individual sample units returned by each *Sample function. The goal of either method is to avoid having collectors teams 'cheat' the system by repeatedly collecting along the border between two or more grid cells. While we understand that many teams may be collecting closely due to the species biology, land management, or other restrictions, the goal of this function is to try and guide them in dispersing there activity.

The method used computes the geometric centroid of each region, if the center falls outside of the grid, it is snapped back onto the nearest location by default. Once the centers of each cell are calculated the remaining area of each grid has distances calculated between the centers and there locations. In final processing n_breaks are applied based on distances from the desired cell center to partition the space into different priority collection units.

Note that if you are submitting data from the ecoregion based sample, the column n, must be maintained.

Usage

PrioritizeSample(x, method, reps, n_breaks, verbose = TRUE)

Arguments

x: an sf/tibble/dataframe. a set of sample grids from any of the *Sample functions
method: Character. The method to use for prioritization. Currently only 'centered' is implemented.
reps: Numeric. The number of repetitions used in the sampling design. This is only used for messaging purposes at this time.
n_breaks: Numeric. The number of breaks to return from the function, defaults to 3. Values much higher than that are untested, and beyond 5 of questionable utility.
verbose: Bool. Whether to print messages to console or not, defaults to TRUE.

Examples

if (FALSE) { # \dontrun{
nc <- sf::st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE) |>
dplyr::select(NAME) |>
  sf::st_transform(5070) # should be in planar coordinate system. 

set.seed(1)
zones <- EqualAreaSample(nc, n = 20, pts = 1000, planar_projection = 32617, reps = 100)

# the function requires an input sampling strategy to create the prioritization areas
ps <- PrioritizeSample(zones$Geometry, method = 'centered', n_breaks = 3)

ggplot2::ggplot() + 
 ggplot2::geom_sf(data = ps,  aes(fill = factor(Level))) +
 ggplot2::geom_sf(data = zones$Geometry, color = 'red', fill = NA, linewidth = 1) 
} # }