R/lsm_c_tca.R

In landscapeecology/landscapemetrics: Landscape Metrics for Categorical Map Patterns

#' TCA (class level)
#'
#' @description Total core area (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{TCA = \sum_{j = 1}^{n} a_{ij}^{core} * (\frac{1} {10000})}
#' where here \eqn{a_{ij}^{core}} is the core area in square meters.
#'
#' TCA is a 'Core area metric' and equals the sum of core areas of all patches belonging
#' to class i. A cell is defined as core area if the cell has no neighbour with a different
#' value than itself (rook's case). In other words, the core area of a patch is all area that
#' is not an edge. It characterises patch areas and shapes of patches belonging to class i
#' simultaneously (more core area when the patch is large and the shape is rather compact,
#' i.e. a square). Additionally, TCA is a measure for the configuration of the landscape,
#' because the sum of edges increase as patches are less aggregated.
#'
#' \subsection{Units}{Hectares}
#' \subsection{Range}{TCA >= 0}
#' \subsection{Behaviour}{Increases, without limit, as patch areas increase
#' and patch shapes simplify. TCA = 0 when every cell in every patch of class i
#' is an edge.}
#'
#' @seealso
#' \code{\link{lsm_p_core}},
#' \code{\link{lsm_l_tca}}
#'
#' @return tibble
#'
#' @examples
#' landscape <- terra::rast(landscapemetrics::landscape)
#' lsm_c_tca(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_c_tca <- function(landscape, directions = 8, consider_boundary = FALSE, edge_depth = 1) {
    landscape <- landscape_as_list(landscape)

    result <- lapply(X = landscape,
                     FUN = lsm_c_tca_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_c_tca_calc <- function(landscape, directions, consider_boundary, edge_depth, resolution, extras = NULL){

    core_area <- lsm_p_core_calc(landscape,
                                 directions = directions,
                                 consider_boundary = consider_boundary,
                                 edge_depth = edge_depth,
                                 resolution = resolution,
                                 extras = extras)

    # all cells are NA
    if (all(is.na(core_area$value))) {
        return(tibble::new_tibble(list(level = "class",
                              class = as.integer(NA),
                              id = as.integer(NA),
                              metric = "tca",
                              value = as.double(NA))))
    }

    core_area <- stats::aggregate(x = core_area[, 5], by = core_area[, 2],
                                  FUN = sum)

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