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.