R/lsm_c_area_sd.R

In landscapemetrics: Landscape Metrics for Categorical Map Patterns

#' AREA_SD (class level)
#'
#' @description Standard deviation of patch area (Area and edge 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{AREA_{SD} = sd(AREA[patch_{ij}])}
#' where \eqn{AREA[patch_{ij}]} is the area of each patch in hectares.
#'
#' AREA_SD is an 'Area and Edge metric'. The metric summarises each class
#' as the standard deviation of all patch areas belonging to class i.
#' The metric describes the differences among patches of the same class i in
#' the landscape.
#'
#' Because the metric is based on distances or areas please make sure your data
#' is valid using \code{\link{check_landscape}}.
#'
#' \subsection{Units}{Hectares}
#' \subsection{Range}{AREA_SD >= 0}
#' \subsection{Behaviour}{Equals AREA_SD = 0 if all patches are identical in size.
#' Increases, without limit, as the variation of patch areas increases.}
#'
#' @seealso
#' \code{\link{lsm_p_area}},
#' \code{\link[stats]{sd}} \cr
#' \code{\link{lsm_c_area_mn}},
#' \code{\link{lsm_c_area_cv}}, \cr
#' \code{\link{lsm_l_area_mn}},
#' \code{\link{lsm_l_area_sd}},
#' \code{\link{lsm_l_area_cv}}
#'
#' @return tibble
#'
#' @examples
#' landscape <- terra::rast(landscapemetrics::landscape)
#' lsm_c_area_sd(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_area_sd <- function(landscape, directions = 8) {
    landscape <- landscape_as_list(landscape)

    result <- lapply(X = landscape,
                     FUN = lsm_c_area_sd_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_area_sd_calc <- function(landscape, directions, resolution, extras = NULL){

    # get area of patches
    area <- lsm_p_area_calc(landscape,
                            directions = directions,
                            resolution = resolution,
                            extras = extras)

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

    # calculate sd
    area_sd <- stats::aggregate(area[, 5], by = area[, 2], FUN = stats::sd)

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