adehabitatLT (version 0.1)

sett0: Round the Timing of Collection of Relocations to Obtain Regular Trajectory

Description

This function rounds the timing of collection of relocations in an object of class ltraj to obtain a regular trajectory, based on a reference date.

Usage

sett0(ltraj, date.ref, dt, correction.xy = c("none", "cs"),
      tol = dt/10, units = c("sec", "min", "hour", "day"), ...)

Arguments

ltraj

an object of class ltraj

date.ref

an object of class POSIXt containing either one reference date (the same for all animals) or n reference dates, where n is the number of bursts in ltraj (see below)

dt

the time lag between relocations

correction.xy

the correction for the coordinates. "none" (default), does not performs any correction. "cs" performs a correction based on the hypothesis that the animal moves at constant speed (see below).

tol

the tolerance, which measures the imprecision in the timing of data collection (see below)

units

the time units for dt and tol

...

additional arguments to be passed to the function rec

Value

• an object of class ltraj containing a regular trajectory.

Details

Trajectories are stored in adehabitatLT as lists of "bursts" of successive relocations with the timing of relocation. Regular trajectories are characterized by a constant time lag dt between successive relocations (don't mix animals located every 10 minutes and animals located every day in a regular trajectory). However, in many cases, the actual time lag in the data may not be equal to the theoretical time lag dt: there may be some negligible imprecision in the time of collection of the data (e.g. an error of a few seconds on a time lag of one hour). But many functions of adehabitatLT require exact regular trajectories. sett0 allows to round the date so that all the successive relocations are separated exactly by dt. The function sett0 requires that the imprecision is at most equal to tol. To proceed, it is necessary to pass a reference date as argument. The reference date is chosen so that the rest of the division of (date.relocations - reference.date) by dt is equal to zero. For example, if it is known that one of the relocations of the trajectory should have been collected on January 16th 1996 at 18H00, and if the theoretical time lag between two relocations is of one hour, the date of reference could be (for example) the August 1st 2017 at 05H00, because these two dates are separated by an exact number of hours. Alternatively, the August 1st 2007 at 05H30 is an uncorrect reference date, because the number of hours separating these two dates is not an integer. Note that this rounding adds an error on the relocation. For example, the position of a moving animal at 17H57 is not the same as its position at 18H00. If the time imprecision in the data collection is negligible (e.g. a few seconds, while dt is equal to an hour), this "noise" in the relocations can be ignored, but if it is more important, a correction on the relocation is needed. The function sett0 may correct the relocations based on the hypothesis of constant speed (which is not necessarily biologically relevant, see examples). Note finally that missing values can be present in the trajectory. Indeed, there are modes of data collection that fail to locate the animal at some dates. These failures should appear as missing values in the regular trajectory. It is often convenient to use the function setNA before the function sett0 to set the missing values in a (nearly) regular trajectory.

See Also

ltraj for additional information on objects of class ltraj, is.regular for regular trajectories, setNA to place missing values in the trajectory and cutltraj to cut a trajectory into several bursts based on a criteria.

Examples

#########################################################################
##
##
## Transform a GPS monitoring on 4 ibex into a regular trajectory
##

data(ibexraw)
is.regular(ibexraw)

## the data are not regular: see the distribution of dt (in hours)
## according to the date

plotltr(ibexraw, "dt/3600")

## The relocations have been collected every 4 hours, and there are some
## missing data

## The reference date: the hour should be exact (i.e. minutes=0):
refda <- strptime("00:00", "%H:%M")
refda

## Set the missing values
ib2 <- setNA(ibexraw, refda, 4, units = "hour") 

## now, look at dt for the bursts:
plotltr(ib2, "dt")

## dt is nearly regular: round the date:

ib3 <- sett0(ib2, refda, 4, units = "hour") 

plotltr(ib3, "dt")
is.regular(ib3)

## ib3 is now regular