R/CoordinateCleaner-package.R

In CoordinateCleaner: Automated Cleaning of Occurrence Records from Biological Collections

#'Global Coastlines buffered by 1 degree
#'
#'  A \code{SpatVector} with global coastlines, with a 1 degree buffer to extent coastlines as alternative reference for \code{\link{cc_sea}}. Can be useful to identify species in the sea, without flagging records in mangroves, marshes, etc.
#'
#' @name buffland
#' @docType data
#' @source 
#' \url{https://www.naturalearthdata.com/downloads/10m-physical-vectors/}
#' @keywords gazetteers
#' @examples
#' 
#' data("buffland")
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#'Global Coastlines buffered by -1 degree
#'
#'  A \code{SpatVector} with global coastlines, with a -1 degree buffer to extent coastlines as alternative reference for \code{\link{cc_sea}}. Can be useful to identify marine species on land without flagging records in estuaries, etc.
#'
#' @name buffsea
#' @docType data
#' @source 
#' \url{https://www.naturalearthdata.com/downloads/10m-physical-vectors/}
#' @keywords gazetteers
#' @examples
#' 
#' data("buffsea")
NULL


#' CoordinateCleaner
#' 
#' Automated Cleaning of Occurrence Records from Biological Collections
#' 
#' Automated flagging of common spatial and temporal errors in biological and
#' paleontological collection data, for the use in conservation, ecology and
#' paleontology. Includes automated tests to easily flag (and exclude) records
#' assigned to country or province centroid, the open ocean, the headquarters of
#' the Global Biodiversity Information Facility, urban areas or the location of
#' biodiversity institutions (museums, zoos, botanical gardens, universities).
#' Furthermore identifies per species outlier coordinates, zero coordinates,
#' identical latitude/longitude and invalid coordinates. Also implements an
#' algorithm to identify data sets with a significant proportion of rounded
#' coordinates. Especially suited for large data sets. See
#' <https://ropensci.github.io/CoordinateCleaner/> for more details and
#' tutorials.
#' 
#' @name CoordinateCleaner-package
#' @aliases CoordinateCleaner-package CoordinateCleaner
#' @docType package
#' @keywords  internal
#' @author Alexander Zizka, Daniele Silvestro, Tobias Andermann, Josue Azevedo, 
#' Camila Duarte Ritter, Daniel Edler, Harith Farooq, Andrei Herdean, Maria Ariza, 
#' Ruud Scharn, Sten Svantesson, Niklas Wengstrom, Vera Zizka 
#' 
NULL



#' Country Centroids and Country Capitals
#' 
#' A \code{data.frame} with coordinates of country and province centroids and
#' country capitals as reference for the \code{\link{clean_coordinates}},
#' \code{\link{cc_cen}} and \code{\link{cc_cap}} functions. Coordinates are
#' based on the Central Intelligence Agency World Factbook
#' \url{https://www.cia.gov/the-world-factbook/},
#' \url{https://thematicmapping.org/downloads/world_borders.php} and geolocate
#' \url{https://geo-locate.org}.
#' 
#' 
#' @name countryref
#' @docType data
#' @format A data frame with 5,305 observations on 13 variables.
#' #' \describe{ 
#' \item{iso3}{ISO-3 code for each country, in case of provinces also referring to the country.}
#' \item{iso2}{ISO-2 code for each country, in case of provinces also referring to the country.} 
#' \item{adm1_code}{adm code for countries and provinces.} 
#' \item{name}{a factor; name of the country or province.} 
#' \item{type}{identifying if the entry refers to a country or province level.} 
#' \item{centroid.lon}{Longitude of the country centroid.}
#' \item{centroid.lat}{Latitude of the country centroid.}
#' \item{capital}{Name of the country capital, empty for provinces.}
#' \item{capital.lon}{Longitude of the country capital.}
#' \item{capital.lat}{Latitude of the country capital.}
#' \item{area_sqkm}{The area of the country or province.}
#' \item{uncertaintyRadiusMeters}{The uncertainty of the country centroid.}
#' \item{source}{The data source. Currently only available for \url{https://geo-locate.org}}}
#' 
#' @source CENTRAL INTELLIGENCE AGENCY (2014) \emph{The World Factbook},
#' Washington, DC.
#' 
#' \url{https://www.cia.gov/the-world-factbook/}
#' \url{https://thematicmapping.org/downloads/world_borders.php}
#' \url{https://geo-locate.org}
#' @keywords gazetteers
#' @examples
#' 
#' data(countryref)
#' head(countryref)
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#' Global Locations of Biodiversity Institutions
#' 
#' A global gazetteer for biodiversity institutions from various sources,
#' including zoos, museums, botanical gardens, GBIF contributors, herbaria,
#' university collections.
#' 
#' 
#' @name institutions
#' @docType data
#' @format A data frame with 12170 observations on 12 variables.
#' @source Compiled from various sources: \itemize{ \item Global Biodiversity
#' Information Facility \url{https://www.gbif.org/} \item Wikipedia
#' \url{https://www.wikipedia.org/} \item Geonames \url{https://www.geonames.org/} \item The Global
#' Registry of Biodiversity Repositories \item Index
#' Herbariorum \url{https://sweetgum.nybg.org/science/ih/}
#' \item Botanic Gardens Conservation International \url{https://www.bgci.org/}
#' }
#' @keywords gazetteers
#' @examples
#' 
#' data(institutions)
#' str(institutions)
#' 
NULL


#' Example data from the Paleobiologydatabase
#' 
#' A dataset of 5000 flowering plant fossil occurrences as example for data of the paleobiology Database, downloaded using the paleobioDB packages as specified in the vignette \dQuote{Cleaning_PBDB_fossils_with_CoordinateCleaner}.
#' 
#' 
#' @name pbdb_example
#' @docType data
#' @format A data frame with 5000 observations on 36 variables.
#' @source \itemize{ 
#' \item The Paleobiology database \url{https://paleobiodb.org/} 
#' \item Sara Varela, Javier Gonzalez Hernandez and Luciano Fabris Sgarbi (2016). 
#' paleobioDB: Download and Process Data from the Paleobiology Database. 
#' R package version 0.5.0. \url{https://CRAN.R-project.org/package=paleobioDB}.
#' }
#' @keywords gazetteers
#' @examples
#' 
#' data(institutions)
#' str(institutions)
#' 
NULL



#' Artificial Hotspot Occurrence Inventory
#'
#'  A data frame with information on Artificial Hotspot Occurrence Inventory (AHOI)
#'  as available in Park et al 2022. For more details see reference.
#'
#' @name aohi
#' @docType data
#' @source 
#' \url{https://onlinelibrary.wiley.com/doi/10.1111/jbi.14543}
#' @keywords gazetteers
#' @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}
#' @examples
#' 
#' data("aohi")
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