tgkde: Time geographic kernel density estimation

In jedalong/wildlifeTG: Time Geograhic Analysis of Wildlife Telemetry Data

Description

Compute the time geographic kernel density estimate of an animals utilization distribution following the methods described in Downs et al. (2011).

Usage

tgkde(traj, disfun = "inv", c2 = 1, grid = NA, ...)

Arguments

traj	an object of the class ltraj which contains the time-stamped movement fixes of the first object. Note this object must be a type II ltraj object. For more information on objects of this type see help(ltraj).
disfun	one of 'inv', 'inv2', 'exp', 'norm' representing the shape of the distance decay function used to model movement probabilities within the geoellipse (see Downs et al. (2011) for more information).
c2	parameter used to control shape of different distance decay functions, default = 1.
grid	spatial resolution (pixel size) of output utilization raster in appropriate units. Default is chosen based on the x and y range of the input telemetry data. Alternatively, a RasterLayer can be passed in upon which the UD is computed.
...	additional parameters to be passed to the function dynvmax. For example, should include options for dynamic and method; see the documentation for dynvmax for more detailed information on what to include here.

Details

The function tgkde can be used to delineate an animals home range using the time geographic kernel density estimation procedure described by Downs et al. (2011). Specifically, it modifies the shape of the traditional kernel to consider the time geographic limits of movement opportunity - termed the geoellipse by Downs, which is analagous to the potential path area concept described by Long & Nelson (2012,2015). Several basic functions – including inverse distance, inverse distance squared, exponential, and normal – can be used to quantify movement probabilities within the geoellipse. The output is then the utilization distribution of the animal, confined to the accessibility space defined by the potential path area home range as in Long & Nelson (2012,2015). The function volras can be used to extract volume contours (e.g., 95

Value

This function returns a RasterLayer representing the utilization distribution of the animal

References

Downs, J.A., Horner, M.W., Tucker, A.D. (2011) Time-geographic density estimation for home range analysis. Annals of GIS. 17(3): 163-171.

See Also

dynvmax, dynppa, volras

Examples

data(m3)
ud <- tgkde(m3,disfun='inv',method='vanderWatt')
raster::plot(ud)

jedalong/wildlifeTG documentation built on July 17, 2019, 2:52 p.m.