Calculate precipitation statistics

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.

Usage

calc_precipitation_wc(engine = "extract", stats = "mean")

Arguments

engine

The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.

stats

Function to be applied to compute statistics for polygons either single or multiple inputs as character. Supported statistics are: "mean", "median", "sd", "min", "max", "sum" "var".

Value

A function that returns an indicator tibble with precipitation statistics as variable and corresponding values as value.

Details

The required resources for this indicator are:

• precipitation layer from worldclim_precipitation

Examples

# \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_worldclim_precipitation(years = 2018)) %>%
  calc_indicators(
    calc_precipitation_wc(
      engine = "extract",
      stats = c("mean", "median")
    )
  ) %>%
  portfolio_long()

aoi
#> Simple feature collection with 24 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: 24 × 9
#>    WDPAID ISO3  assetid indicator       datetime            variable unit  value
#>     <dbl> <chr>   <int> <chr>           <dttm>              <chr>    <chr> <dbl>
#>  1 478140 DOM         1 precipitation_… 2018-01-01 00:00:00 worldcl… mm     26.7
#>  2 478140 DOM         1 precipitation_… 2018-01-01 00:00:00 worldcl… mm     26.7
#>  3 478140 DOM         1 precipitation_… 2018-02-01 00:00:00 worldcl… mm     26.1
#>  4 478140 DOM         1 precipitation_… 2018-02-01 00:00:00 worldcl… mm     26.5
#>  5 478140 DOM         1 precipitation_… 2018-03-01 00:00:00 worldcl… mm     66.7
#>  6 478140 DOM         1 precipitation_… 2018-03-01 00:00:00 worldcl… mm     68.6
#>  7 478140 DOM         1 precipitation_… 2018-04-01 00:00:00 worldcl… mm     82.0
#>  8 478140 DOM         1 precipitation_… 2018-04-01 00:00:00 worldcl… mm     82.1
#>  9 478140 DOM         1 precipitation_… 2018-05-01 00:00:00 worldcl… mm    330. 
#> 10 478140 DOM         1 precipitation_… 2018-05-01 00:00:00 worldcl… mm    338. 
#> # ℹ 14 more rows
#> # ℹ 1 more variable: geom <POLYGON [°]>
# }