Download e-Stat administrative boundaries as an sf object

Fetches official e-Stat census boundary polygons and returns them as an sf object with an area_code column matching the codes used by get_estat(), so the two join cleanly. Boundaries are derived from e-Stat's authoritative small-area (町丁・字) shapefiles and dissolved to the requested level.

Usage

estat_boundaries(
  areas = NULL,
  level = c("municipality", "prefecture", "small_area"),
  year = 2020,
  datum = c("2000", "2011"),
  cache = TRUE,
  designated_cities = c("both", "ward", "city")
)

Arguments

areas: Character vector of area codes selecting which prefectures to download: 2-digit prefecture codes (e.g. "31") or any codes whose first two digits are a prefecture (e.g. a 5-digit "31201" or the area_code column from get_estat()). NULL downloads all 47 prefectures (large).
level: Geographic level to return: "municipality" (default; 5-digit PREF+CITY) or "prefecture" (dissolved whole prefectures, PREF+"000") or "small_area" (raw 町丁・字, 9-digit KEY_CODE).
year: Census year of the boundaries (e.g. 2020, 2015). Match this to the census year of your data: municipality codes and boundaries change between censuses (mergers), so a mismatched year can mis-join.
datum: Geodetic datum: "2000" (JGD2000, EPSG:4612, default) or "2011" (JGD2011, EPSG:6668).
cache: If TRUE (default), cache downloaded boundary files under estat_cache_dir().
designated_cities: How to handle the 20 ordinance-designated cities and Tokyo's special wards at level = "municipality", since e-Stat's shapefiles carry only ward codes: "both" (default) returns ward polygons and a unioned parent-city polygon (e.g. both 01101… and 01100 札幌市), so data coded at either level joins; "ward" returns wards only; "city" returns the parent city only. Ignored for other levels.

Value

An sf object with area_code, name columns, and geometry.

Details

Requires the sf package. Downloaded files are cached (see estat_cache_dir()).

Examples

if (FALSE) { # \dontrun{
# Municipalities of Tottori (prefecture 31), 2020 census boundaries
bnd <- estat_boundaries("31", level = "municipality", year = 2020)
} # }