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Build a local geography layer from Census TIGER/Line boundaries

Source: R/build-local-geography.R
build_local_geography.Rd

Downloads an authoritative Census boundary layer for a state with the tigris package and standardises it into the two-column schema add_local_geography() expects: location_county (always from counties) and location_locality (from the requested geography). It also carries stable Census identifiers such as county_fips, municipality_geoid, and muni_join_key when those fields exist. This makes "locality" a configurable concept, because what counts as a municipality is not consistent across states.

Usage

build_local_geography(
  state,
  geography = c("county_subdivision", "place", "county", "tract"),
  county = NULL,
  year = NULL,
  cb = TRUE,
  ...
)

Arguments

state

Two-letter state abbreviation or FIPS code (passed to tigris).

geography

Which Census layer becomes location_locality. One of "county_subdivision", "place", "county", "tract".

county

Optional county filter (name or FIPS) for "county_subdivision"/"tract"; passed to tigris.

year

Vintage year for the boundary files. NULL uses the tigris default.

cb

If TRUE (default), use the smaller cartographic boundary files; FALSE pulls the full-resolution TIGER/Line files.

...

Passed through to the underlying tigris download function.

Value

An sf polygon layer in WGS84 (EPSG:4326) with location_county, location_locality, stable join-code columns when available, and geometry, ready for add_local_geography(geography_shapes = ...).

Details

Choosing geography:

  • "county_subdivision" (default) maps well to townships/municipalities in states like NJ, PA, NY and New England. Best general default for "locality".

  • "place" maps to incorporated places and CDPs, but misses townships and many unincorporated areas. Places can also straddle counties, so each place is assigned the county it overlaps most.

  • "county" sets locality to the county itself.

  • "tract" uses the census tract identifier as the locality (analysis, not administrative naming).

Census TIGER/Line is the best scalable baseline nationwide. For high-stakes, state-specific reporting where "municipality" has legal meaning, prefer an official state GIS layer and pass it straight to add_local_geography() - that path works regardless, since the join accepts any polygon layer.

Examples

if (interactive()) {
areas <- build_local_geography(state = "PA", geography = "county_subdivision")
final <- add_local_geography(geocoded, geography_shapes = areas)
}