redistribution_kernel: Create a redistribution kernel
In amt: Animal Movement Tools

redistribution_kernel

R Documentation

Create a redistribution kernel

Description

From a fitted integrated step-selection function for a given position a redistribution kernel is calculated (i.e., the product of the movement kernel and the selection function).

Usage

redistribution_kernel(
  x = make_issf_model(),
  start = make_start(),
  map,
  fun = function(xy, map) {
     extract_covariates(xy, map, where = "both")
 },
  covars = NULL,
  max.dist = get_max_dist(x),
  n.control = 1e+06,
  n.sample = 1,
  landscape = "continuous",
  compensate.movement = landscape == "discrete",
  normalize = TRUE,
  interpolate = FALSE,
  as.rast = FALSE,
  tolerance.outside = 0
)

Arguments

`x`	`⁠[fit_issf]⁠` A fitted integrated step-selection function. Generated either with `fit_issf()` or make `make_issf_model()`.
`start`	`⁠[sim_start]⁠` The start position in space and time. See `make_start()`.
`map`	`⁠[SpatRaster]⁠` A SpatRaster with all covariates.
`fun`	`⁠[function]⁠` A function that is executed on each location of the redistribution kernel. The default function is `extract_covariates()`.
`covars`	`⁠[tibble]⁠` Additional covariates that might be used in the model (e.g., time of day).
`max.dist`	`⁠[numeric(1)]⁠` The maximum distance of the redistribution kernel.
`n.control`	`⁠[integer(1)]{1e6}⁠` The number of points of the redistribution kernel (this is only important if `landscape = "continuous"`).
`n.sample`	`⁠[integer(1)]{1}⁠` The number of points sampled from the redistribution kernel (this is only important if `as.rast = FALSE`).
`landscape`	`⁠[character(1)]{"continuous"}⁠` If `⁠"continuous⁠` the redistribution kernel is sampled using a random sample of size `n.control`. If `landscape = "discrete"` each cell in the redistribution kernel is used.
`compensate.movement`	`⁠[logical(1)]⁠` Indicates if movement parameters are corrected or not. This only relevant if `landscape = 'discrete'`.
`normalize`	`⁠[logical(1)]{TRUE}⁠` If `TRUE` the redistribution kernel is normalized to sum to one.
`interpolate`	`⁠[logical(1)]{FALSE}⁠` If `TRUE` a stochastic redistribution kernel is interpolated to return a raster layer. Note, this is just for completeness and is computationally inefficient in most situations.
`as.rast`	`⁠[logical(1)]{TRUE}⁠` If `TRUE` a `SpatRaster` should be returned.
`tolerance.outside`	`⁠[numeric(1)]{0}⁠` The proportion of the redistribution kernel that is allowed to be outside the `map`.