SDLfilter (version 2.0.0)

dupfilter: Filter temporal and/or spatial duplicates

Description

Function to filter temporal and spatial duplicates in tracking data and retain only a single fix per time and location.

Usage

dupfilter(sdata, step.time = 0, step.dist = 0, conditional = FALSE)

Arguments

sdata

A data frame containing columns with the following headers: "id", "DateTime", "lat", "lon", "qi". The function filters the input data by the unique "id". "DateTime" is date & time in class POSIXct. "lat" and "lon" are the latitude and longitude of each location in decimal degrees. "qi" is the numerical quality index associated with each location fix where a greater number indicates a higher accuracy (e.g. the number of GPS satellites involved in estimation).

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.

Value

The input data frame is returned containing only a single fix (latitude/longitude pair) per time and location.

Details

This function filters temporal and spatial duplicates in tracking data. It first filters temporally and spatially exact locations. It then looks for temporal duplicates and retains a fix with the highest quality index. When temporal or spatial duplicates are associated with the same quality index, the function retains a location that is nearest from a previous and to a subsequent location.

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_exact, dupfilter_qi, dupfilter_time, dupfilter_space, track_param

Examples

# NOT RUN {
#### Load data sets
## Fastloc GPS data obtained from a green turtle
data(turtle)


#### Apply dupfilter
turtle.dup <- dupfilter(turtle)
# }