Function reference • CoordinateCleaner

Wrapper functions

clean_coordinates(): Geographic Cleaning of Coordinates from Biologic Collections

clean_dataset(): Coordinate Cleaning using Dataset Properties

clean_fossils(): Geographic and Temporal Cleaning of Records from Fossil Collections

Geographic coordinate cleaning

cc_aohi(): Identify Coordinates in Artificial Hotspot Occurrence Inventory

cc_cap(): Identify Coordinates in Vicinity of Country Capitals.

cc_cen(): Identify Coordinates in Vicinity of Country and Province Centroids

cc_coun(): Identify Coordinates Outside their Reported Country

cc_dupl(): Identify Duplicated Records

cc_equ(): Identify Records with Identical lat/lon

cc_gbif(): Identify Records Assigned to GBIF Headquarters

cc_inst(): Identify Records in the Vicinity of Biodiversity Institutions

cc_iucn(): Identify Records Outside Natural Ranges

cc_outl(): Identify Geographic Outliers in Species Distributions

cc_sea(): Identify Non-terrestrial Coordinates

cc_urb(): Identify Records Inside Urban Areas

cc_val(): Identify Invalid lat/lon Coordinates

cc_zero(): Identify Zero Coordinates

Dataset-levelcleaning

cd_ddmm(): Identify Datasets with a Degree Conversion Error

cd_round(): Identify Datasets with Rasterized Coordinates

Fossil cleaning

cf_age(): Identify Fossils with Outlier Age

cf_equal(): Identify Fossils with equal min and max age

cf_outl(): Identify Outlier Records in Space and Time

cf_range(): Identify Fossils with Extreme Age Ranges

write_pyrate(): Create Input Files for PyRate

Data

buffland: Global Coastlines buffered by 1 degree

buffsea: Global Coastlines buffered by -1 degree

countryref: Country Centroids and Country Capitals

institutions: Global Locations of Biodiversity Institutions

pbdb_example: Example data from the Paleobiologydatabase

aohi: Artificial Hotspot Occurrence Inventory

Visualization

plot(<spatialvalid>): Plot Method for Class Spatialvalid

Check

is.spatialvalid(): Check spatialvalid object