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Check if a dataset is gridded

Source: R/dataset_gridded.R
dataset_gridded.Rd

Check if a dataset is gridded

Usage

dataset_gridded(
  uuid = NULL,
  min_dis = 0.05,
  min_per = 50,
  min_dis_count = 30,
  return = "logical",
  warn = TRUE
)

Arguments

uuid

(vector) A character vector of GBIF datasetkey uuids.

min_dis

(numeric) (default 0.02) Minimum distance in degrees to accept as gridded.

min_per

(integer)(default 50%) Minimum percentage of points having same nearest neighbor distance to be considered gridded.

min_dis_count

(default 30) Minimum number of unique points to accept an assessment of 'griddyness'.

return

(character) (default "logical"). Choice of "data" will return a data.frame of more information or "logical" will return just TRUE or FALSE indicating whether a dataset is considered 'gridded".

warn

(logical) indicates whether to warn about missing values or bad values.

Value

A logical vector indicating whether a dataset is considered gridded. Or if return="data", a data.frame of more information.

Details

Gridded datasets are a known problem at GBIF. Many datasets have equally-spaced points in a regular pattern. These datasets are usually systematic national surveys or data taken from some atlas (“so-called rasterized collection designs”). This function uses the percentage of unique lat-long points with the most common nearest neighbor distance to identify gridded datasets.

https://data-blog.gbif.org/post/finding-gridded-datasets/

I recommend keeping the default values for the parameters.

Examples

if (FALSE) { # \dontrun{

dataset_gridded("9070a460-0c6e-11dd-84d2-b8a03c50a862")
dataset_gridded(c("9070a460-0c6e-11dd-84d2-b8a03c50a862",
               "13b70480-bd69-11dd-b15f-b8a03c50a862"))


} # }