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Process drought index data

Source: R/process.R
process_drought.Rd

The process_drought() function imports and cleans raw drought index files returned by download_drought(), producing a harmonized output object ready for calculate_drought():

  • SPEI / EDDI — returns a SpatRaster with one layer per time step, layer names in "<source>_<timescale>_YYYY-MM-DD" format, CRS set to EPSG:4326.

  • USDM — returns a SpatVector (polygon) with columns DM (drought-monitor class, integer 0–4), date (Date), and source ("usdm"), CRS EPSG:4326.

Usage

process_drought(
  source = c("spei", "eddi", "usdm"),
  path = NULL,
  date = c("2020-01-01", "2020-12-31"),
  timescale = 1L,
  extent = NULL,
  ...
)

Arguments

source

character(1). Drought data source. One of "spei", "eddi", or "usdm". When called through process_covariates(covariate = "spei") the alias is forwarded automatically.

path

character(1). Directory containing downloaded drought files (output of download_drought()).

date

character(1 or 2). Single date or start/end dates. Format "YYYY-MM-DD".

timescale

integer(1). Accumulation timescale in months (SPEI/EDDI only; ignored for USDM). Must match the timescale used in download_drought(). Default 1L.

extent

numeric(4) or SpatExtent. Optional spatial crop applied before returning. NULL (default) returns full extent.

...

Reserved for future use; currently ignored.

Value

  • SpatRaster for SPEI or EDDI sources.

  • SpatVector (polygons) for USDM source.

Note

  • SPEI/EDDI files are expected to follow the naming convention produced by download_drought(): spei<timescale>.nc and either legacy eddi<timescale>mn<year>.nc or current EDDI_ETrs_<timescale>mn_<YYYYMMDD>.asc.

  • USDM files are expected to be weekly shapefiles named USDM_<YYYYMMDD>.shp.

  • Layer/column naming is standardised so that calculate_drought() can operate identically regardless of source.

See also

download_drought, calculate_drought

Author

Insang Song

Examples

if (FALSE) { # \dontrun{
## SPEI
spei <- process_drought(
  source = "spei",
  path = "./data/drought",
  date = c("2020-01-01", "2020-12-31"),
  timescale = 1L
)
## USDM
usdm <- process_drought(
  source = "usdm",
  path = "./data/drought",
  date = c("2020-01-07", "2020-03-31")
)
} # }