continentOutlieRs: Flag continent-level outliers with a provided checklist.

In BeeBDC: Occurrence Data Cleaning

Flag continent-level outliers with a provided checklist.

Description

This function flags continent-level outliers using the checklist provided with this package. For additional context and column names, see beesChecklist().

Usage

continentOutlieRs(
  checklist = NULL,
  data = NULL,
  keepAdjacentContinent = FALSE,
  pointBuffer = NULL,
  scale = 50,
  stepSize = 1e+06,
  mc.cores = 1
)

Arguments

checklist	A data frame or tibble. The formatted checklist which was built based on the Discover Life website.
data	A data frame or tibble. The a Darwin Core occurrence dataset.
keepAdjacentContinent	Logical. If TRUE, occurrences in continents that are adjacent to checklist continents will be kept. If FALSE, they will be flagged. Defualt = FALSE.
pointBuffer	Numeric. A buffer around points to help them align with a continent or coastline. This provides a good way to retain points that occur right along the coast or borders of the maps in rnaturalearth
scale	Numeric. The value fed into the map scale parameter for rnaturalearth::ne_countries()'s scale parameter: Scale of map to return, one of 110, 50, 10 or 'small', 'medium', 'large', where smaller numbers are higher resolution. WARNING: This function is tested on 110 and 50.
stepSize	Numeric. The number of occurrences to process in each chunk. Default = 1000000.
mc.cores	Numeric. If > 1, the function will run in parallel using mclapply using the number of cores specified. If = 1 then it will be run using a serial loop. NOTE: Windows machines must use a value of 1 (see ?parallel::mclapply). Additionally, be aware that each thread can use large chunks of memory. If the cores throw issues, consider setting mc.cores to 1. Default = 1.

Value

The input data with two new columns, .continentOutlier or .sea. There are three possible values for the new column: TRUE == passed, FALSE == failed (not in continent or in the ocean), NA == did not overlap with rnaturalearth map.

See Also

countryOutlieRs() for implementation at the country level. Country-level implementation will be more data-hungry and, where data do not yet exist, difficult to implement. Additionally, see beesChecklist() for input data. Note, not all columns are necessary if you are building your own dataset. At a minimum you will need validName and continent.

Examples

if(requireNamespace("rnaturalearthdata")){
library(magrittr)
  # Load in the test dataset
beesRaw <- BeeBDC::beesRaw
  # For the sake of this example, use the testChecklist
system.file("extdata", "testChecklist.rda", package="BeeBDC") |> load()
  # For real examples, you might download the beesChecklist from FigShare using 
  #  [BeeBDC::beesChecklist()]

beesRaw_out <- continentOutlieRs(checklist = testChecklist,
                               data = beesRaw %>%
                               dplyr::filter(dplyr::row_number() %in% 1:50),
                               keepAdjacentContinent = FALSE,
                               pointBuffer = 1,
                               scale = 50,
                               stepSize = 1000000,
                               mc.cores = 1)
table(beesRaw_out$.continentOutlier, useNA = "always")
} # END if require

BeeBDC documentation built on Nov. 4, 2024, 9:06 a.m.