cc_aohi {CoordinateCleaner} | R Documentation |
Identify Coordinates in Artificial Hotspot Occurrence Inventory
Description
Removes or flags records within Artificial Hotspot Occurrence Inventory. Poorly geo-referenced occurrence records in biological databases are often erroneously geo-referenced to highly recurring coordinates that were assessed by Park et al 2022. See the reference for more details.
Usage
cc_aohi(
x,
lon = "decimalLongitude",
lat = "decimalLatitude",
species = "species",
taxa = c("Aves", "Insecta", "Mammalia", "Plantae"),
buffer = 10000,
geod = TRUE,
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. |
taxa |
Artificial Hotspot Occurrence Inventory (AHOI) were created based on four different taxa, birds, insecta, mammalia, and plantae. Users can choose to keep all, or any specific taxa subset to define the AHOI locations. Default is to keep all: c("Aves", "Insecta", "Mammalia", "Plantae"). |
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. Default = TRUE. See https://seethedatablog.wordpress.com/ for detail and credits. |
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.
References
Park, D. S., Xie, Y., Thammavong, H. T., Tulaiha, R., & Feng, X. (2023). Artificial Hotspot Occurrence Inventory (AHOI). Journal of Biogeography, 50, 441–449. doi:10.1111/jbi.14543
See Also
Other Coordinates:
cc_cap()
,
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 = c(runif(99, -180, 180), -47.92),
decimalLatitude = c(runif(99, -90,90), -15.78))
cc_aohi(x)