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Reads the Geocoded Peacekeeping Operations (Geo-PKO) data

Source: R/data_geopko.R
read_geopko.Rd

Downloads and processes Geo-PKO (Geocoded Peacekeeping Operations) data, which provides spatial and temporal information on UN peacekeeping deployments worldwide. The function formats coordinates as spatial geometries and standardizes temporal variables for analysis.

Usage

read_geopko()

Value

A sf object

Details

The dataset contains information on peacekeeping deployments including mission details, troop numbers, deployment locations, and temporal coverage. This enables analysis of peacekeeping presence, intensity, and geographic distribution over time.

Geo-PKO tracks the locations and timing of UN peacekeeping operations at high spatial and temporal resolution. This function:

  • Downloads the Geo-PKO dataset from the data repository

  • Filters out records with missing coordinate information

  • Converts longitude/latitude coordinates to sf point geometries

  • Sets coordinate reference system to WGS84 (EPSG:4326)

  • Creates standardized date variables (mydate) from year-month information

  • Rolls dates forward to the last day of each month for consistency

References

Cil D, Fjelde H, Hultman L, Nilsson D (2020). “Mapping Blue Helmets: Introducing the Geocoded Peacekeeping Operations (Geo-PKO) Dataset.” Journal of Peace Research, 57(2), 360–370. ISSN 0022-3433, 1460-3578, doi:10.1177/0022343319871978 , 2024-10-21.

Examples

if (FALSE) { # \dontrun{
# Read Geo-PKO data
geopko_data <- read_geopko()

# Examine the structure
print(geopko_data)
str(geopko_data)

# Check available columns
names(geopko_data)

# View temporal coverage
range(geopko_data$mydate, na.rm = TRUE)

# Examine unique missions
if("mission" %in% names(geopko_data)) {
  unique_missions <- unique(geopko_data$mission)
  head(sort(unique_missions), 10)
}

# Plot peacekeeping deployment locations
plot(sf::st_geometry(geopko_data),
     main = "UN Peacekeeping Deployment Locations",
     pch = 16, cex = 0.5)

# Filter to specific time period
recent_deployments <- geopko_data[geopko_data$mydate >= as.Date("2010-01-01"), ]
plot(sf::st_geometry(recent_deployments),
     main = "Recent Peacekeeping Deployments (2010+)",
     pch = 16, cex = 0.5)

# Analyze deployment intensity by year
geopko_data$year_deployed <- lubridate::year(geopko_data$mydate)
yearly_deployments <- table(geopko_data$year_deployed)
plot(names(yearly_deployments), yearly_deployments,
     type = "l", main = "Peacekeeping Deployments Over Time",
     xlab = "Year", ylab = "Number of Deployments")

# Filter to specific mission (example)
# monusco_data <- geopko_data[grepl("MONUSCO", geopko_data$mission), ]
# plot(sf::st_geometry(monusco_data), main = "MONUSCO Deployments")
} # }