Identify Zero Coordinates

Removes or flags records with either zero longitude or latitude and a radius around the point at zero longitude and zero latitude. These problems are often due to erroneous data-entry or geo-referencing and can lead to typical patterns of high diversity around the equator.

cc_zero(
  x,
  lon = "decimalLongitude",
  lat = "decimalLatitude",
  buffer = 0.5,
  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”.

buffer

numerical. The buffer around the 0/0 point, where records should be flagged as problematic, in decimal degrees. Default = 0.5.

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_aohi(), cc_cap(), cc_cen(), cc_coun(), cc_dupl(), cc_equ(), cc_gbif(), cc_inst(), cc_iucn(), cc_outl(), cc_sea(), cc_urb(), cc_val()

Examples

x <- data.frame(species = "A", 
                decimalLongitude = c(0,34.84, 0, 33.98), 
                decimalLatitude = c(23.08, 0, 0, 15.98))
                
cc_zero(x)
#> Testing zero coordinates
#> Removed 3 records.
#>   species decimalLongitude decimalLatitude
#> 4       A            33.98           15.98
cc_zero(x, value = "flagged")
#> Testing zero coordinates
#> Flagged 3 records.
#> [1] FALSE FALSE FALSE  TRUE