#' Get the land mask for a dataset.
#'
#' Get the land mask for a dataset, either for the whole series or for specific
#' time points.
#'
#' @param time_bp time slices in years before present (negative values represent
#' time before present, positive values time in the future). This parameter can
#' be a vector of times (the slices need
#' to exist in the dataset), a list with a min and max element setting the
#' range of values, or left to NULL to retrieve all time steps.
#' To check which slices are available, you can use
#' [get_time_bp_steps()].
#' @param time_ce time in years CE as an alternative to `time_bp`.Only one of
#' `time_bp` or `time_ce` should be used. For available time slices in years CE, use
#' [get_time_ce_steps()].
#' @param dataset string defining dataset to be downloaded (a list of possible
#' values can be obtained with [list_available_datasets()]). This function
#' will not work on custom datasets.
#' @returns a binary [`terra::SpatRaster`] with the land mask as 1s
#'
#' @import terra
#' @export
get_land_mask <- function(time_bp = NULL, time_ce = NULL, dataset) {
time_bp <- check_time_vars(time_bp = time_bp, time_ce = time_ce)
if (!dataset %in% list_available_datasets()) {
stop(
"this function only works on the defaults datasets in pastclim\n",
"you can get a list with `list_available_datasets()`"
)
}
if (dataset %in% c("Example", "Beyer2020", "Krapp2021")) {
climate_series <- region_series(
time_bp = time_bp, bio_variables = "biome",
dataset = dataset
)
land_mask <- climate_series["biome"]
land_mask[land_mask < 0] <- NA
land_mask[land_mask != 28] <- 1
land_mask[land_mask == 28] <- NA
} else if (any(grepl("WorldClim", dataset),
grepl("paleoclim", dataset))) {
climate_series <- region_series(
time_bp = time_bp,
bio_variables = get_vars_for_dataset(dataset)[1],
dataset = dataset
)
land_mask <- climate_series[[1]]
land_mask[!is.na(land_mask)] <- 1
} else {
stop("this method has not been yet developed for this dataset")
}
# sort out categories
# we pass a list so that each level if turned into a categorical variable
levels(land_mask) <-
rep(list(data.frame(id=1, category= c("land"))),
terra::nlyr(land_mask))
terra::coltab(land_mask) <- rep (list(
data.frame(
values = c(1),
cols = c("#1C540F")
)
), terra::nlyr(land_mask))
if (is.null(time_ce)) {
names(land_mask) <- paste("land_mask", time_bp(land_mask), sep = "_")
} else {
names(land_mask) <- paste("land_mask", time(land_mask), sep = "_")
}
varnames(land_mask) <- "land_mask"
return(land_mask)
}
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