dupfilter_space {SDLfilter} | R Documentation |
Filter spatial duplicates
Description
Function to filter spatial duplicates in tracking data.
Usage
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 |
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. |
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.
Value
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.
Note
A minimum of two locations per id is required.
Author(s)
Takahiro Shimada
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 doi:10.1007/s00227-015-2771-0
See Also
dupfilter
, dupfilter_exact
, dupfilter_time
, dupfilter_qi
, track_param