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rank_individual_coverage_gains() calculates the marginal coverage gain from adding each candidate area to an existing coverage network one at a time.

Usage

rank_individual_coverage_gains(
  candidate_areas,
  existing_areas = NULL,
  population_geography,
  coverage_vars,
  geography_id = NULL,
  method = c("intersection", "centroid", "areal"),
  crs = 5070
)

Arguments

candidate_areas

An sf object containing candidate catchment geometries to evaluate one at a time.

existing_areas

An sf object containing the existing catchment geometries, or NULL if there is no existing network.

population_geography

An sf object containing the population or burden geography to summarize. This object should contain the columns named in coverage_vars.

coverage_vars

Character vector of numeric column names in population_geography to summarize.

geography_id

Optional character string naming an identifier column in population_geography. Passed to calculate_geography_coverage_gain().

method

Character string specifying how geographic coverage should be calculated. One of "intersection", "centroid", or "areal".

crs

Coordinate reference system to use for spatial calculations. Defaults to EPSG:5070.

Value

If coverage_vars has length 1, a tibble with one row per candidate area. If coverage_vars has length greater than 1, a named list of tibbles split by coverage_var. Each tibble includes the coverage summaries returned by calculate_geography_coverage_gain(), the non-geometry columns from candidate_areas, and a rank column ordered by descending newly_covered.

Details

This is a convenience wrapper around calculate_geography_coverage_gain(). It is useful for ranking candidate catchment areas, such as buffers or travel-time isochrones, by the population or burden newly covered after accounting for overlap with an existing network.

The function assumes that candidate_areas and existing_areas already contain the catchment geometries to evaluate. It does not create buffers, travel-time isochrones, or other catchment areas internally.