#' Calculate population count statistics
#'
#' WorldPop, which was initiated in 2013, offers easy access to spatial demographic
#' datasets, claiming to use peer-reviewed and fully transparent methods to create
#' global mosaics for the years 2000 to 2020. This function allows to efficiently
#' calculate population count statistics (e.g. total number of population) for
#' polygons. For each polygon, the desired statistic/s (min, max, sum, mean,
#' median, sd or var) is/are returned.
#'
#' The required resources for this indicator are:
#' - [worldpop]
#'
#' @name population_count
#' @param engine The preferred processing functions from either one of "zonal",
#' "extract" or "exactextract" as character.
#' @param stats Function to be applied to compute statistics for polygons
#' either one or multiple inputs as character "min", "max", "sum", "mean", "median"
#' "sd" or "var".
#' @keywords indicator
#' @returns A function that returns an indicator tibble with the specified
#' populations statistics as variable and the corresponding values as value.
#' @include register.R
#' @export
#' @examples
#' \dontshow{
#' mapme.biodiversity:::.copy_resource_dir(file.path(tempdir(), "mapme-data"))
#' }
#' \dontrun{
#' library(sf)
#' library(mapme.biodiversity)
#'
#' outdir <- file.path(tempdir(), "mapme-data")
#' dir.create(outdir, showWarnings = FALSE)
#'
#' mapme_options(
#' outdir = outdir,
#' verbose = FALSE
#' )
#'
#' aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
#' package = "mapme.biodiversity"
#' ) %>%
#' read_sf() %>%
#' get_resources(get_worldpop(years = 2010:2020)) %>%
#' calc_indicators(
#' calc_population_count(engine = "extract", stats = c("sum", "median"))
#' ) %>%
#' portfolio_long()
#'
#' aoi
#' }
calc_population_count <- function(engine = "extract", stats = "sum") {
engine <- check_engine(engine)
stats <- check_stats(stats)
function(x,
worldpop = NULL,
name = "population_count",
mode = "asset",
aggregation = "stat",
verbose = mapme_options()[["verbose"]]) {
if (is.null(worldpop)) {
return(NULL)
}
# set max value of 65535 to NA
worldpop <- clamp(
worldpop,
lower = -Inf,
upper = 65534,
values = FALSE
)
results <- select_engine(
x = x,
raster = worldpop,
stats = stats,
engine = engine,
name = "population",
mode = "asset"
)
years <- unlist(lapply(names(worldpop), function(x) strsplit(x, "_")[[1]][2]))
results[["datetime"]] <- as.POSIXct(paste0(years, "-01-01T00:00:00Z"))
results[["unit"]] <- "count"
results %>%
tidyr::pivot_longer(-c(datetime, unit), names_to = "variable", values_to = "value") %>%
dplyr::select(datetime, variable, unit, value)
}
}
register_indicator(
name = "population_count",
description = "Statistic of population counts",
resources = "worldpop"
)
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