Skip to contents

Sample from a circle using the Uniform distribution

Source: R/sample_from_uniform_circle.R
sample_from_uniform_circle.Rd

This function samples a new observations point of a species within the uncertainty circle around each observation assuming a Uniform distribution.

Usage

sample_from_uniform_circle(observations, missing_uncertainty = 1000, seed = NA)

Arguments

observations

An sf object with POINT geometry and a time_point and coordinateUncertaintyInMeters column. If the former column is not present, the function will assume a single time point. If the latter column is not present, the function will assume no uncertainty (zero meters) around the observation points.

missing_uncertainty

A positive numeric value (default: 1000 m) used to replace missing (NA) values in the coordinateUncertaintyInMeters column. This ensures that all observations have a defined uncertainty radius for sampling. Only applied when the column is present but contains NA values; if the column itself is absent, a value of 0 is assumed instead.

seed

A positive numeric value setting the seed for random number generation to ensure reproducibility. If NA (default), then set.seed() is not called at all. If not NA, then the random number generator state is reset (to the state before calling this function) upon exiting this function.

Value

An sf object with POINT geometry containing the locations of the sampled occurrences and a coordinateUncertaintyInMeters column containing the coordinate uncertainty for each observation.

See also

Other designation: sample_from_binormal_circle()

Examples

library(sf)
library(dplyr)

# Create four random points
n_points <- 4
xlim <- c(3841000, 3842000)
ylim <- c(3110000, 3112000)
coordinate_uncertainty <- rgamma(n_points, shape = 5, rate = 0.1)

observations_sf <- data.frame(
  lat = runif(n_points, ylim[1], ylim[2]),
  long = runif(n_points, xlim[1], xlim[2]),
  time_point = 1,
  coordinateUncertaintyInMeters = coordinate_uncertainty
) %>%
  st_as_sf(coords = c("long", "lat"), crs = 3035)

# Sample points within uncertainty circles according to uniform rules
sample_from_uniform_circle(
  observations = observations_sf,
  seed = 123
)
#> Simple feature collection with 4 features and 2 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 3841221 ymin: 3110351 xmax: 3841969 ymax: 3111434
#> Projected CRS: ETRS89-extended / LAEA Europe
#> # A tibble: 4 × 3
#> # Rowwise: 
#>   time_point coordinateUncertaintyInMeters          geometry
#>        <dbl>                         <dbl>       <POINT [m]>
#> 1          1                          79.0 (3841348 3110876)
#> 2          1                          60.2 (3841221 3111434)
#> 3          1                          19.0 (3841969 3110726)
#> 4          1                          77.0 (3841456 3110351)