austFilter: Filter satellite locations

Description

Apply a three stage algorithm to eliminate erroneous locations, based on the procedure outlined in Austin et al. (2003).

Usage

austFilter(time, lon, lat, id=gl(1, 1, length(time)),
           speedthres, distthres, window=5)
grpSpeedFilter(x, speedthres, window=5)
rmsDistFilter(x, speedthres, window=5, distthres)

Arguments

time

POSIXct object with dates and times for each point.

lon

numeric vectors of longitudes, in decimal degrees.

lat

numeric vector of latitudes, in decimal degrees.

a factor grouping points in different categories (e.g. individuals).

speedthres

speed threshold (m/s) above which filter tests should fail any given point.

distthres

distance threshold above which the last filter test should fail any given point.

window

integer indicating the size of the moving window over which tests should be carried out.

3-column matrix with column 1: POSIXct vector; column 2: numeric longitude vector; column 3: numeric latitude vector.

Value

A matrix with three columns of logical vectors with values TRUE for points that failed each stage. Results from each filter are presented independently of the others; i.e. points marked as failing one filter are not necessarily marked as failing the next one.

Warning

This function applies McConnell et al.'s filter as described in Austin et al. (2003), but other authors may have used the filter differently. Austin et al. (2003) have apparently applied the filter in a vectorized manner. It is not clear from the original paper whether the filter is applied iteratively or in a vectorized fashion, so authors may be using it inconsistently.

Details

These functions implement the location filtering procedure outlined in Austin et al. (2003). grpSpeedFilter and rmsDistFilter can be used to perform only the first stage or the second and third stages of the algorithm on their own, respectively. Alternatively, the three filters can be run sequentially using austFilter.

The first stage of the filter is an iterative process which tests every point, except the first and last two, for travel velocity relative to the preceeding/following two points. If all these four speeds are greater than the specified threshold, the point is marked as failing the first stage. In this case, the next point is tested, removing the failing point from the set of test points.

The second stage runs McConnell et al. (1992) algorithm, which tests all the points that passed the first stage, in the same manner as above. The root mean square of all four speeds is calculated, and if it is greater than the specified threshold, the point is marked as failing the second stage.

The third stage is run simultaneously with the second stage, but if the mean distance of all four pairs of points is greater than the specified threshold, then the point is marked as failing the third stage.

References

McConnell BJ, Chambers C, Fedak MA. 1992. Foraging ecology of southern elephant seals in relation to bathymetry and productivity of the Southern Ocean. Antarctic Science 4:393-398.

Austin D, McMillan JI, Bowen D. 2003. A three-stage algorithm for filtering erroneous Argos satellite locations. Marine Mammal Science 19: 371-383.