fatalities_acled {mapme.biodiversity}R Documentation

Calculate number of fatalities of conflict events from ACLED

Description

The indicator aggregated the number of fatalities within a given asset on a monthly cadence stratified either by event type, sub-event type or disorder type. To learn about the different categorisation ACLED uses to encode events please consult ACLED's codebook.

Usage

calc_fatalities_acled(
  years = 2000,
  stratum = c("event_type", "sub_event_type", "disorder_type"),
  precision_location = 1,
  precision_time = 1
)

Arguments

years

A numeric vector indicating the years for which to summarize fatalities.

stratum

A character vector indicating the stratification to be applied. Should be one of "event_type", "sub_event_type", or "disorder_type". Defaults to "event_type".

precision_location

A numeric indicating precision value for the geolocation up to which events are included. Defaults to 1.

precision_time

A numeric indicating the precision value of the temporal coding up to which events are included. Defaults to 1.

Details

The required resources for this indicator are:

You may apply quality filters based on the precision of the geolocation of events and the temporal precision. By default, these are set to only include events with the highest precision scores.

For geo-precision there are levels 1 to 3 with decreasing accuracy:

For temporal precision there are levels 1 to 3 with decreasing precision:

Value

A function that returns an indicator tibble with the type of violence as variable and counts of civilian fatalities as value.

References

Raleigh, C., Kishi, R. & Linke, A. Political instability patterns are obscured by conflict dataset scope conditions, sources, and coding choices. Humanit Soc Sci Commun 10, 74 (2023). doi:10.1057/s41599-023-01559-4

Examples


## Not run: 
library(sf)
library(mapme.biodiversity)

outdir <- file.path(tempdir(), "mapme-data")
dir.create(outdir, showWarnings = FALSE)

mapme_options(
  outdir = outdir,
  verbose = FALSE,
  chunk_size = 1e8
)

aoi <- system.file("extdata", "burundi.gpkg",
  package = "mapme.biodiversity"
) %>%
  read_sf() %>%
  get_resources(get_acled(years = 2020)) %>%
  calc_indicators(
    calc_fatalities_acled(
      years = 2020,
      precision_location = 1,
      precision_time = 1
    )
  ) %>%
  portfolio_long()

aoi

## End(Not run)

[Package mapme.biodiversity version 0.9.4 Index]