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#' DIVISION (class level)
#'
#' @description Landscape division index (Aggregation metric)
#'
#' @param landscape A categorical raster object: SpatRaster; Raster* Layer, Stack, Brick; stars or a list of SpatRasters.
#' @param directions The number of directions in which patches should be connected: 4 (rook's case) or 8 (queen's case).
#'
#' @details
#' \deqn{DIVISON = (1 - \sum \limits_{j = 1}^{n} (\frac{a_{ij}} {A}) ^ 2)}
#' where \eqn{a_{ij}} is the area in square meters and \eqn{A} is the total
#' landscape area in square meters.
#'
#' DIVISION is an 'Aggregation metric. It can be in as the probability that two
#' randomly selected cells are not located in the same patch of class i. The landscape
#' division index is negatively correlated with the effective mesh size (\code{\link{lsm_c_mesh}}).
#'
#' Because the metric is based on distances or areas please make sure your data
#' is valid using \code{\link{check_landscape}}.
#'
#' \subsection{Units}{Proportion }
#' \subsection{Ranges}{0 <= Division < 1}
#' \subsection{Behaviour}{Equals DIVISION = 0 if only one patch is present. Approaches
#' DIVISION = 1 if all patches of class i are single cells.}
#'
#' @seealso
#' \code{\link{lsm_p_area}},
#' \code{\link{lsm_l_ta}}, \cr
#' \code{\link{lsm_l_division}}
#'
#' @return tibble
#'
#' @examples
#' landscape <- terra::rast(landscapemetrics::landscape)
#' lsm_c_division(landscape)
#'
#' @references
#' McGarigal K., SA Cushman, and E Ene. 2023. FRAGSTATS v4: Spatial Pattern Analysis
#' Program for Categorical Maps. Computer software program produced by the authors;
#' available at the following web site: https://www.fragstats.org
#'
#' Jaeger, J. A. 2000. Landscape division, splitting index, and effective mesh
#' size: new measures of landscape fragmentation.
#' Landscape ecology, 15(2), 115-130.
#'
#' @export
lsm_c_division <- function(landscape, directions = 8) {
landscape <- landscape_as_list(landscape)
result <- lapply(X = landscape,
FUN = lsm_c_division_calc,
directions = directions)
layer <- rep(seq_along(result),
vapply(result, nrow, FUN.VALUE = integer(1)))
result <- do.call(rbind, result)
tibble::add_column(result, layer, .before = TRUE)
}
lsm_c_division_calc <- function(landscape, directions, resolution, extras = NULL) {
# get patch area
patch_area <- lsm_p_area_calc(landscape,
directions = directions,
resolution = resolution,
extras = extras)
# get total area
total_area <- sum(patch_area$value)
# all values NA
if (is.na(total_area)) {
return(tibble::new_tibble(list(level = "class",
class = as.integer(NA),
id = as.integer(NA),
metric = "division",
value = as.double(NA))))
}
# calculate division for each patch
patch_area$value <- (patch_area$value / total_area) ^ 2
# summarise for classes
division <- stats::aggregate(x = patch_area[, 5], by = patch_area[, 2],
FUN = sum)
division$value <- 1 - division$value
return(tibble::new_tibble(list(
level = rep("class", nrow(division)),
class = as.integer(division$class),
id = rep(as.integer(NA), nrow(division)),
metric = rep("division", nrow(division)),
value = as.double(division$value)
)))
}
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