This function allows to efficiently calculate the relative wetness in the shallow groundwater section with regard to the the 1948-2012 reference period. The values represent the wetness percentile a given area achieves at a given point in time in regard to the reference period. For each polygon, the desired statistic/s (mean, median or sd) is/are returned. The required resources for this indicator are:
Details
The following arguments can be set:
- stats_drought
Function to be applied to compute statistics for polygons either one or multiple inputs as character "mean", "median" or "sd".
- engine
The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.
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)
aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
package = "mapme.biodiversity"
) %>%
read_sf() %>%
init_portfolio(
years = 2022,
outdir = outdir,
tmpdir = tempdir(),
add_resources = FALSE,
verbose = FALSE
) %>%
get_resources("nasa_grace") %>%
calc_indicators("drought_indicator",
stats_drought = c("mean", "median"),
engine = "extract"
) %>%
tidyr::unnest(drought_indicator)
#> Error in map2(.x, vec_index(.x), .f, ...): ℹ In index: 1.
#> ℹ With name: nasa_grace.
#> Caused by error in `.read_raster_source()`:
#> ! Did not find equal number of tiles per timestep.
aoi
#> Error in eval(expr, envir, enclos): object 'aoi' not found
# }