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Calculate distance to nearest land-contiguous border (bdist1)

Source: R/data_cshapes.R
bdist1.Rd

Computes the spherical distance (in kilometers) from each PRIO-GRID cell centroid to the border of the nearest land-contiguous neighboring country using CShapes 2.0 boundary data. This implies that cells in e.g. Northern Denmark are measured to the border to Germany even if the straight-line distance to Norway (across international waters) is shorter. Cells belonging to island states with no contiguous neighboring country (e.g., New Zealand) are coded as missing. Islands within states are still measured.

Usage

bdist1(measurement_date, cshp = read_cshapes(), past_result = NULL)

Arguments

measurement_date

A single Date object specifying the date for boundary analysis. Must be within CShapes temporal coverage.

cshp

An sf object containing CShapes 2.0 boundary data. Defaults to read_cshapes() if not provided.

past_result

A list object from a previous bdist1 calculation. If boundaries haven't changed, the function returns this result directly, avoiding recomputation. Default is NULL.

Value

A list containing three elements:

  • bdist1: A SpatRaster with distances (km) from cell centroids to nearest international borders, masked to state system coverage

  • boundaries: An sf object with country boundary line geometries

Details

The function includes optimization logic that reuses previous calculations if country boundaries haven't changed since the last computation, significantly reducing processing time for temporal sequences.

Distance calculations use spherical geometry (S2) for accurate measurements across the globe, particularly important for high-latitude regions.

References

Schvitz G, Girardin L, Rüegger S, Weidmann NB, Cederman L, Gleditsch KS (2022). “Mapping the International System, 1886-2019: The CShapes 2.0 Dataset.” Journal of Conflict Resolution, 66(1), 144–161. ISSN 0022-0027, doi:10.1177/00220027211013563 , 2024-11-22.

Examples

if (FALSE) { # \dontrun{
# Calculate border distances for 2010
border_dist_2010 <- bdist1(as.Date("2010-01-01"))
} # }