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These functions allow to calculated statistics based on the harmonized carbon layers for 2010 and 2018 by Noon et al. (2022).
calc_irr_carbon(
type = c("total", "soil", "biomass", "all"),
engine = "extract",
stats = "mean"
)calc_man_carbon(
type = c("total", "soil", "biomass", "all"),
engine = "extract",
stats = "mean"
)
calc_vul_carbon(
type = c("total", "soil", "biomass", "all"),
engine = "extract",
stats = "mean"
)
A function that returns an indicator tibble with (type)_carbon_(stat)
as variable and the respective statistic (in Mg) as value.
One of "total", "soil", "biomass", "all". Determines for which data layer the statistics are calculated.
The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.
Function to be applied to compute statistics for polygons either one or multiple inputs as character. Supported statistics are: "mean", "median", "sd", "min", "max", "sum", and "var".
The required resources for these indicators are:
carbon_resources
Irrecoverable carbon is the amount of carbon that, if lost today, could not be recovered until 2050. It can be calculated for above- and below-ground carbon, the total amount of carbon, or for all layers.
Manageable carbon is the amount of carbon that, in principle, is manageable by human activities, e.g. its release to the atmosphere can be prevented. It can be calculated for above- and below-ground carbon, the total amount of carbon, or for all layers.
Vulnerable carbon is the amount of carbon that would be released in a typical land conversion activity. It can be calculated for above- and below-ground carbon, the total amount of carbon, or for all layers.
# \dontshow{
mapme.biodiversity:::.copy_resource_dir(file.path(tempdir(), "mapme-data"))
# }
if (FALSE) {
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", "shell_beach_protected_area_41057_B.gpkg",
package = "mapme.biodiversity"
) %>%
read_sf() %>%
get_resources(
get_man_carbon(),
get_vul_carbon(),
get_irr_carbon()
) %>%
calc_indicators(
calc_man_carbon(stats = "sum"),
calc_vul_carbon(stats = "sum"),
calc_irr_carbon(stats = "sum")
) %>%
portfolio_long()
aoi
}
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