spd_filter: Filters out detections based on maximum speed over distance
In bsmity13/ADePTR: Acoustic Detection Processing and Visualization Tool in R

Description Usage Arguments Details References See Also Examples

Filters detections that would imply an unreasonably high swim speed over a sufficiently large distance.

1 2	spd_filter(proc_det, max_speed = units::set_units(10, "m/s"), min_dist = units::set_units(1, "km"))

`proc_det`	A `data.frame` of class `dets` as returned by the function `proc_dets()`.
`max_speed`	An object of class `units` setting the maximum speed with which an animal can move between two receivers that are at least `min_dist` apart.
`min_dist`	An object of class `units` setting the minimum distance two receivers must be apart to consider the speed filter.

False-positive detections in acoustic data can occur for reasons related to signal collisions. Type A false detections are detections of IDs that are not present in the study system, and here we assume the user has already removed these detections prior to using this package. Type B false detections occur when a signal is erroneously decoded as the signal of a different tag that is in the study system – these detections are much harder to distinguish from true detections and are the focus of this function.

Determining the maximum speed an animal can move is not as straightforward as it first seems. Animals can move at very high speeds for very short bursts, but most often cannot sustain those high speeds over longer distances. Also, with the considerable position error that can result from assuming a detected animal is at the location of the acoustic station, an animal sitting in the middle of two receivers and being detected simultaneously by both can seem like an animal moving with impossible speed.

Simpfendorfer, C. A., C. Huveneers, A. Steckenreuter, K. Tattersall, X. Hoenner, R. Harcourt, and M.R. Heupel. (2015). Ghosts in the data: false detections in VEMCO pulse position modulation acoustic telemetry monitoring equipment. Animal Biotelemetry 3:55.

See Simpfendorfer et al. (2015) for details about false detections in acoustic telemetry.

#Load the example data set
data(acoustic)

#Process detections
proc.det <- proc_dets(det = acoustic$detections, sta = acoustic$stations)

#Apply the speed filter with default max_speed and min_dist
det.filt <- spd_filter(proc.det)