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Calculate drought indicator statistics

Source: R/calc_drought_indicator.R
drought_indicator.Rd

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.

Usage

calc_drought_indicator(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 one or multiple inputs as character "mean", "median" or "sd".

Value

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

Details

The required resources for this indicator are:

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_nasa_grace(years = 2022)) %>%
  calc_indicators(
    calc_drought_indicator(
      engine = "extract",
      stats = c("mean", "median")
    )
  ) %>%
  portfolio_long()

aoi
#> Simple feature collection with 40 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: 40 × 9
#>    WDPAID ISO3  assetid indicator       datetime            variable unit  value
#>     <dbl> <chr>   <int> <chr>           <dttm>              <chr>    <chr> <dbl>
#>  1 478140 DOM         1 drought_indica… 2022-01-03 00:00:00 wetness… perc…  57.5
#>  2 478140 DOM         1 drought_indica… 2022-01-03 00:00:00 wetness… perc…  57.5
#>  3 478140 DOM         1 drought_indica… 2022-01-10 00:00:00 wetness… perc…  55.5
#>  4 478140 DOM         1 drought_indica… 2022-01-10 00:00:00 wetness… perc…  55.5
#>  5 478140 DOM         1 drought_indica… 2022-01-17 00:00:00 wetness… perc…  54  
#>  6 478140 DOM         1 drought_indica… 2022-01-17 00:00:00 wetness… perc…  54  
#>  7 478140 DOM         1 drought_indica… 2022-01-24 00:00:00 wetness… perc…  53  
#>  8 478140 DOM         1 drought_indica… 2022-01-24 00:00:00 wetness… perc…  53  
#>  9 478140 DOM         1 drought_indica… 2022-01-31 00:00:00 wetness… perc…  43.5
#> 10 478140 DOM         1 drought_indica… 2022-01-31 00:00:00 wetness… perc…  43.5
#> # ℹ 30 more rows
#> # ℹ 1 more variable: geom <POLYGON [°]>
# }