#' CONTAG (landscape level)
#'
#' @description Contagion (Aggregation metric)
#'
#' @param landscape A categorical raster object: SpatRaster; Raster* Layer, Stack, Brick; stars or a list of SpatRasters.
#' @param verbose Print warning message if not sufficient patches are present
#'
#' @details
#' \deqn{CONTAG = 1 + \frac{\sum \limits_{q = 1}^{n_{a}} p_{q} ln(p_{q})}{2ln(t)}}
#'
#' where \eqn{p_{q}} the adjacency table for all classes divided by the sum of that table and
#' \eqn{t} the number of classes in the landscape.
#'
#' CONTAG is an 'Aggregation metric'. It is based on cell adjacencies and describes
#' the probability of two random cells belonging to the same class. \eqn{p_{q}} is
#' the cell adjacency table, where the order is preserved and pairs of adjacent cells
#' are counted twice. Contagion is affected by both the dispersion and interspersion
#' of classes. E.g., low class dispersion (= high proportion of like adjacencies) and
#' low interspersion (= uneven distribution of pairwise adjacencies) lead to a high
#' contagion value.
#'
#' The number of classes to calculate CONTAG must be >= than 2.
#'
#' \subsection{Units}{Percent}
#' \subsection{Range}{0 < Contag <=100}
#' \subsection{Behaviour}{Approaches CONTAG = 0 if all cells are unevenly distributed
#' and 100 indicates that all cells are equally adjacent to all other classes.}
#'
#' @return tibble
#'
#' @examples
#' landscape <- terra::rast(landscapemetrics::landscape)
#' lsm_l_contag(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
#'
#' Riitters, K.H., O'Neill, R.V., Wickham, J.D. & Jones, K.B. (1996). A note on
#' contagion indices for landscape analysis. Landscape ecology, 11, 197-202.
#'
#' @export
lsm_l_contag <- function(landscape, verbose = TRUE) {
landscape <- landscape_as_list(landscape)
result <- lapply(X = landscape,
FUN = lsm_l_contag_calc,
verbose = verbose)
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_contag_calc <- function(landscape, verbose, extras = NULL) {
# convert to raster to matrix
if (!inherits(x = landscape, what = "matrix")) {
landscape <-terra::as.matrix(landscape, wide = TRUE)
}
# all values NA
if (all(is.na(landscape))) {
return(tibble::new_tibble(list(level = "landscape",
class = as.integer(NA),
id = as.integer(NA),
metric = "contag",
value = as.double(NA))))
}
if (!is.null(extras)){
t <- length(extras$classes)
} else {
t <- length(get_unique_values_int(landscape, verbose = FALSE))
}
if (t < 2) {
if (verbose) {
warning("Number of classes must be >= 2: CONTAG = NA.",
call. = FALSE)
}
return(tibble::new_tibble(list(level = "landscape",
class = as.integer(NA),
id = as.integer(NA),
metric = "contag",
value = as.double(NA))))
} else {
if (!is.null(extras)){
adjacencies <- extras$neighbor_matrix
} else {
adjacencies <- rcpp_get_coocurrence_matrix(landscape, as.matrix(4))
}
esum <- sum(adjacencies / sum(adjacencies) *
log(adjacencies / sum(adjacencies)), na.rm = TRUE)
emax <- 2 * log(t)
contag <- (1 + esum / emax) * 100
return(tibble::new_tibble(list(level = rep("landscape", length(contag)),
class = rep(as.integer(NA), length(contag)),
id = rep(as.integer(NA), length(contag)),
metric = rep("contag", length(contag)),
value = as.double(contag))))
}
}
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