This function thins a dataset so that only observations that have a distance from each other greater than "dist_min" in space and "interval_min" in time are retained.
thin_by_dist_time(
data,
dist_min,
interval_min,
coords = NULL,
time_col = "time",
lubridate_fun = c,
dist_method = c("great_circle", "euclidean")
)An object of class sf::sf or data.frame, the same as "data".
An sf::sf data frame, or a data frame with coordinate
variables. These can be defined in coords, unless they have standard
names (see details below).
Minimum distance between points (in units appropriate for the projection, or meters for lonlat data).
Minimum time interval between points, in days.
A vector of length two giving the names of the "x" and "y"
coordinates, as found in data. If left to NULL, the function will try to
guess the columns based on standard names c("x", "y"), c("X","Y"),
c("longitude", "latitude"), or c("lon", "lat")
The name of the column with time; if time is not a lubridate
object, use lubridate_fun to provide a function that can be used to
convert appropriately
function to convert the time column into a lubridate object
method to compute distance, either "euclidean" or "great_circle". Defaults to "great_circle", which is more accurate but takes slightly longer.
Geographic distances are measured in the appropriate units for the projection
used. In case of raw latitude and longitude (e.g. as provided in a
data.frame), the crs is set to WGS84, and units are set to meters. Time
interval are estimated in days. Note that for very long time period, the
simple conversion x years = 365 * x days might lead to slightly shorter
intervals than expected, as it ignores leap years. The function y2d()
provides a closer approximation.
This function an algorithm analogous to spThin, with the exception that
neighbours are defined in terms of both space and time.