thin_points: Spatial Correction - Spatially thin records

In gatoRs: Geographic and Taxonomic Occurrence R-Based Scrubbing

Spatial Correction - Spatially thin records

Description

The thin_points function returns records based on coordinate thinning based on a minimum nearest neighbor distance approach.

Usage

thin_points(
  df,
  accepted.name = NA,
  distance = 5,
  reps = 100,
  latitude = "latitude",
  longitude = "longitude"
)

Arguments

df	Data frame of occurrence records.
accepted.name	Accepted name of your species. This argument is not required if the data frame already contains an accepted_name column.
distance	Default = 5. Distance in km to separate records.
reps	Default = 100. Number of times to perform thinning algorithm.
latitude	Default = "latitude". The name of the latitude column in the data frame.
longitude	Default = "longitude". The name of the longitude column in the data frame.

Details

This function is a wrapper for spatial thinning using the spThin package (Aiello-Lammens et al., 2015) In summary, the thinning algorithm provided by spThin calculates the pairwise distances between data points, then randomly samples a single point from all points less than or equal to the set minimum nearest neighbor distance. This process is repeated until the pairwise distances among points do not fall below the minimum nearest neighbor distance.

Value

df is a data frame with the cleaned data. Information about the columns in the returned data frame can be found in the documentation for gators_download().

Examples

thinned_data <- thin_points(data, accepted.name = "Galax urceolata")

gatoRs documentation built on May 29, 2024, 7:11 a.m.