This function allows to efficiently calculate precipitation statistics from Worldclim 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:
precipitation layer from worldclim
Details
The following arguments can be set:
- stats_worldclim
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" "var".
- engine
The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.
Examples
library(sf)
library(mapme.biodiversity)
temp_loc <- file.path(tempdir(), "mapme.biodiversity")
if (!file.exists(temp_loc)) {
dir.create(temp_loc)
resource_dir <- system.file("res", package = "mapme.biodiversity")
file.copy(resource_dir, temp_loc, recursive = TRUE)
}
(try(aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
package = "mapme.biodiversity"
) %>%
read_sf() %>%
init_portfolio(
years = 2018,
outdir = file.path(temp_loc, "res"),
tmpdir = tempdir(),
add_resources = FALSE,
verbose = FALSE
) %>%
get_resources("worldclim_precipitation") %>%
calc_indicators("precipitation_wc",
stats_worldclim = c("mean", "median"),
engine = "extract"
) %>%
tidyr::unnest(precipitation_wc)))
#> Simple feature collection with 12 features and 8 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: -71.80933 ymin: 18.57668 xmax: -71.33201 ymax: 18.69931
#> Geodetic CRS: WGS 84
#> # A tibble: 12 × 9
#> WDPAID NAME DESIG_ENG ISO3 assetid prec_mean prec_median date
#> <dbl> <chr> <chr> <chr> <int> <dbl> <dbl> <date>
#> 1 478140 Sierra de Ne… National… DOM 1 26.9 26.8 2018-01-01
#> 2 478140 Sierra de Ne… National… DOM 1 26.3 26.6 2018-02-01
#> 3 478140 Sierra de Ne… National… DOM 1 66.8 68.8 2018-03-01
#> 4 478140 Sierra de Ne… National… DOM 1 81.8 81.9 2018-04-01
#> 5 478140 Sierra de Ne… National… DOM 1 327. 336. 2018-05-01
#> 6 478140 Sierra de Ne… National… DOM 1 76.0 77.5 2018-06-01
#> 7 478140 Sierra de Ne… National… DOM 1 98.9 98.5 2018-07-01
#> 8 478140 Sierra de Ne… National… DOM 1 106. 108. 2018-08-01
#> 9 478140 Sierra de Ne… National… DOM 1 214. 217. 2018-09-01
#> 10 478140 Sierra de Ne… National… DOM 1 165. 174. 2018-10-01
#> 11 478140 Sierra de Ne… National… DOM 1 60.7 61.9 2018-11-01
#> 12 478140 Sierra de Ne… National… DOM 1 24.9 26.5 2018-12-01
#> # ℹ 1 more variable: geom <POLYGON [°]>