R/lsm_l_dcad.R

In r-spatialecology/landscapemetrics: Landscape Metrics for Categorical Map Patterns

#' DCAD (landscape level)
#
#' @description Disjunct core area density (core area 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).
#' @param consider_boundary Logical if cells that only neighbour the landscape
#' boundary should be considered as core
#' @param edge_depth Distance (in cells) a cell has the be away from the patch
#' edge to be considered as core cell
#'
#' @details
#' \deqn{DCAD = (\frac{\sum \limits_{i = 1}^{m} \sum \limits_{j = 1}^{n} n_{ij}^{core}} {A}) * 10000 * 100}
#' where \eqn{n_{ij}^{core}} is the number of disjunct core areas and \eqn{A}
#' is the total landscape area in square meters.
#'
#' DCAD is a 'Core area metric'. It equals the number of disjunct core areas per
#' 100 ha relative to the total area. A disjunct core area is a 'patch within
#' the patch' containing only core cells. A cell is defined as core area if the cell has no
#' neighbour with a different value than itself (rook's case). The metric is relative and
#' therefore comparable among landscapes with different total areas.
#'
#' \subsection{Units}{Number per 100 hectares}
#' \subsection{Range}{DCAD >= 0}
#' \subsection{Behaviour}{Equals DCAD = 0 when DCORE = 0, i.e. no patch contains
#' a disjunct core area. Increases, without limit, as disjunct core areas become more
#' present, i.e. patches becoming larger and less complex.}
#'
#' @seealso
#' \code{\link{lsm_c_ndca}},
#' \code{\link{lsm_l_ta}}, \cr
#' \code{\link{lsm_c_dcad}}
#'
#' @return tibble
#'
#' @examples
#' landscape <- terra::rast(landscapemetrics::landscape)
#' lsm_l_dcad(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
#'
#' @export
lsm_l_dcad <- function(landscape,
                            directions = 8,
                            consider_boundary = FALSE,
                            edge_depth = 1) {
    landscape <- landscape_as_list(landscape)

    result <- lapply(X = landscape,
                     FUN = lsm_l_dcad_calc,
                     directions = directions,
                     consider_boundary = consider_boundary,
                     edge_depth = edge_depth)

    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_l_dcad_calc <- function(landscape, directions, consider_boundary, edge_depth, resolution, extras = NULL){

    # get patch area
    patch_area <- lsm_p_area_calc(landscape,
                                  directions = directions,
                                  resolution = resolution,
                                  extras = extras)

    # summarise to total area
    total_area <- sum(patch_area$value)

    # all values NA
    if (is.na(total_area)) {
        return(tibble::new_tibble(list(level = "landscape",
                              class = as.integer(NA),
                              id = as.integer(NA),
                              metric = "dcad",
                              value = as.double(NA))))
    }

    # get core areas for each patch
    ncore_patch <- lsm_p_ncore_calc(landscape,
                                    directions = directions,
                                    consider_boundary = consider_boundary,
                                    edge_depth = edge_depth,
                                    resolution = resolution,
                                    extras = extras)

    # summarise for total landscape
    dcad <- sum(ncore_patch$value) / total_area * 100

    return(tibble::new_tibble(list(level = rep("landscape", length(dcad)),
                 class = rep(as.integer(NA), length(dcad)),
                 id = rep(as.integer(NA), length(dcad)),
                 metric = rep("dcad", length(dcad)),
                 value = as.double(dcad))))
}