dupfilter_space function

Filter spatial duplicates

Function to filter spatial duplicates in tracking data.

dupfilter_space(
  sdata,
  step.time = 0,
  step.dist = 0,
  conditional = FALSE,
  no.cores = 1
)

Arguments

• sdata: A data frame containing columns with the following headers: "id", "DateTime", "lat", "lon", "qi". See the data turtle for an example. The function filters the input data by a unique "id" (e.g. transmitter number, identifier for each animal). "DateTime" is the GMT date & time of each location in class POSIXct or character with the following format "2012-06-03 01:33:46". "lat" and "lon" are the latitude and longitude of each location in decimal degrees. "qi" is the quality index associated with each location fix. The input values can be either the number of GPS satellites or Argos Location Classes. Argos Location Classes will be converted to numerical values, where "A", "B", "Z" will be replaced with "-1", "-2", "-3" respectively. The greater number indicates a higher accuracy.
• step.time: Consecutive locations less than or equal to step.time apart are considered temporal duplicates. Default is 0 hours.
• step.dist: Consecutive locations less than or equal to step.dist apart are considered spatial duplicates. Default is 0 kilometres.
• conditional: If TRUE, spatial duplicates are filtered only if they are less than or equal to step.time apart. Default is FALSE.
• no.cores: An integer specifying the number of cores used for parallel computing. Alternatively, type in 'detect' to use the maximum number of available cores minus one.

Returns

The input data frame is returned with spatial duplicates removed. The following columns are added: "pTime", "sTime", "pDist", "sDist". "pTime" and "sTime" are hours from a previous and to a subsequent fix respectively. "pDist" and "sDist" are straight distances in kilometres from a previous and to a subsequent fix respectively.

Details

This function is a partial component of dupfilter, although works as a stand-alone function. First it identifies spatial duplicates by searching for consecutive fixes that were located within step.dist. For each group of spatial duplicates, the function then retains a single fix that is nearest from a previous and to a subsequent location.

Note

A minimum of two locations per id is required.

References

Shimada T, Limpus C, Jones R, Hazel J, Groom R, Hamann M (2016) Sea turtles return home after intentional displacement from coastal foraging areas. Marine Biology 163:1-14 tools:::Rd_expr_doi("10.1007/s00227-015-2771-0")

See Also

dupfilter, dupfilter_exact, dupfilter_time, dupfilter_qi, track_param

Author(s)

Takahiro Shimada