cc_cap {CoordinateCleaner}R Documentation

Identify Coordinates in Vicinity of Country Capitals.

Description

Removes or flags records within a certain radius around country capitals. Poorly geo-referenced occurrence records in biological databases are often erroneously geo-referenced to capitals.

Usage

cc_cap(
  x,
  lon = "decimallongitude",
  lat = "decimallatitude",
  species = "species",
  buffer = 10000,
  geod = TRUE,
  ref = NULL,
  verify = FALSE,
  value = "clean",
  verbose = TRUE
)

Arguments

x

data.frame. Containing geographical coordinates and species names.

lon

character string. The column with the longitude coordinates. Default = “decimallongitude”.

lat

character string. The column with the latitude coordinates. Default = “decimallatitude”.

species

character string. The column with the species identity. Only required if verify = TRUE.

buffer

The buffer around each capital coordinate (the centre of the city), where records should be flagged as problematic. Units depend on geod. Default = 10 kilometres.

geod

logical. If TRUE the radius around each capital is calculated based on a sphere, buffer is in meters and independent of latitude. If FALSE the radius is calculated assuming planar coordinates and varies slightly with latitude, in this case buffer is in degrees. Default = TRUE. See https://seethedatablog.wordpress.com/ for detail and credits.

ref

SpatialPointsDataFrame. Providing the geographic gazetteer. Can be any SpatialPointsDataFrame, but the structure must be identical to countryref. Default = countryref.

verify

logical. If TRUE records are only flagged if they are the only record in a given species flagged close to a given reference. If FALSE, the distance is the only criterion

value

character string. Defining the output value. See value.

verbose

logical. If TRUE reports the name of the test and the number of records flagged.

Value

Depending on the ‘value’ argument, either a data.frame containing the records considered correct by the test (“clean”) or a logical vector (“flagged”), with TRUE = test passed and FALSE = test failed/potentially problematic . Default = “clean”.

Note

See https://ropensci.github.io/CoordinateCleaner/ for more details and tutorials.

See Also

Other Coordinates: cc_cen(), cc_coun(), cc_dupl(), cc_equ(), cc_gbif(), cc_inst(), cc_iucn(), cc_outl(), cc_sea(), cc_urb(), cc_val(), cc_zero()

Examples


x <- data.frame(species = letters[1:10], 
                decimallongitude = runif(100, -180, 180), 
                decimallatitude = runif(100, -90,90))

cc_cap(x)
cc_cap(x, value = "flagged")


[Package CoordinateCleaner version 2.0-20 Index]