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Clean occurrence coordinates

geo_clean.Rd

Flags and optionally filters occurrence records using tests rebuilt inside tidymapr, so callers never need CoordinateCleaner. Flags cover equal longitude and latitude, zero coordinates, country capitals, the GBIF headquarters, biodiversity institutions, points at sea (when a land mask is supplied), geographic outliers, invalid coordinates and duplicates.

Usage

geo_clean(
  data,
  lon = lon,
  lat = lat,
  species = NULL,
  tests = c("equal", "zeros", "capitals", "gbif", "institutions", "validity",
    "duplicates", "outliers"),
  capitals_rad = 10000,
  institutions_rad = 100,
  gbif_rad = 1000,
  outliers_method = c("quantile", "mad"),
  outliers_mtp = 5,
  land_mask = NULL,
  value = c("clean", "flagged", "both")
)

Arguments

data

A data frame of occurrence records.

lon, lat

<data-masking> Coordinate columns.

species

<data-masking> Optional species column for duplicate and outlier tests.

tests

Character vector of tests to run. See Details.

capitals_rad, institutions_rad, gbif_rad

Buffer radius in metres around reference points (defaults match CoordinateCleaner).

outliers_method

"quantile" or "mad".

outliers_mtp

Multiplier for the outlier threshold (quantile IQR or MAD).

land_mask

Optional sf/SpatVector polygons of land, or a SpatRaster land mask. When NULL, the "seas" test is skipped.

value

"clean" (filtered data), "flagged" (logical matrix of flags plus coordinates), or "both" (a list).

Value

Depending on value: a tibble, a flagged tibble, or a list with clean and flagged.

Details

Available tests: "equal", "zeros", "capitals", "centroids" (treated as capitals for the bundled reference set), "gbif", "institutions", "seas", "outliers", "validity", "duplicates".

References

Zizka, A. et al. (2019). CoordinateCleaner: standardized cleaning of occurrence records from biological collection databases. Methods in Ecology and Evolution, 10, 744-751. doi:10.1111/2041-210X.13152

Examples

occ <- tibble::tibble(
  species = c("a", "a", "b", "b", "c"),
  lon = c(147.1, 147.1, 0, 12.58, 151),
  lat = c(-9.4, -9.4, 0, 55.67, -33.9)
)
geo_clean(occ, lon, lat, species = species, value = "flagged")
#> # A tibble: 5 × 12
#>   species   lon   lat .val  .equ  .zer  .cap  .gbf  .inst .dpl  .otl  .summary
#>   <chr>   <dbl> <dbl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl>   
#> 1 a       147.   -9.4 FALSE FALSE FALSE FALSE FALSE FALSE TRUE  FALSE FALSE   
#> 2 a       147.   -9.4 FALSE FALSE FALSE FALSE FALSE FALSE TRUE  FALSE TRUE    
#> 3 b         0     0   FALSE TRUE  TRUE  FALSE FALSE FALSE FALSE FALSE TRUE    
#> 4 b        12.6  55.7 FALSE FALSE FALSE FALSE TRUE  FALSE FALSE FALSE TRUE    
#> 5 c       151   -33.9 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE