sf
polygons and pointsReturns polygons and points corresponding to cities, greater cities and metropolitan areas included on the Urban Audit report of Eurostat.
gisco_get_urban_audit(
year = "2020",
epsg = "4326",
cache = TRUE,
update_cache = FALSE,
cache_dir = NULL,
verbose = FALSE,
spatialtype = "RG",
country = NULL,
level = NULL
)
Release year of the file. One of "2001", "2004", "2014", "2018" or "2020".
projection of the map: 4-digit EPSG code. One of:
"4258": ETRS89
"4326": WGS84
"3035": ETRS89 / ETRS-LAEA
"3857": Pseudo-Mercator
A logical whether to do caching. Default is TRUE
. See
About caching.
A logical whether to update cache. Default is FALSE
.
When set to TRUE
it would force a fresh download of the source
.geojson file.
A path to a cache directory. See About caching.
Logical, displays information. Useful for debugging,
default is FALSE
.
Type of geometry to be returned:
"LB": Labels - POINT
object.
"RG": Regions - MULTIPOLYGON/POLYGON
object.
Optional. A character vector of country codes. It could be
either a vector of country names, a vector of ISO3 country codes or a
vector of Eurostat country codes. Mixed types (as c("Turkey","US","FRA")
)
would not work. See also countrycode::countrycode()
.
Level of Urban Audit. Possible values are "CITIES", "FUA",
"GREATER_CITIES" or NULL
, that would download the full dataset.
A sf
object specified by spatialtype
.
You can set your cache_dir
with gisco_set_cache_dir()
.
Sometimes cached files may be corrupt. On that case, try re-downloading
the data setting update_cache = TRUE
.
If you experience any problem on download, try to download the
corresponding .geojson file by any other method and save it on your
cache_dir
. Use the option verbose = TRUE
for debugging the API query.
For a complete list of files available check gisco_db.
gisco_get_communes()
, gisco_get_lau()
Other political:
gisco_bulk_download()
,
gisco_get_coastallines()
,
gisco_get_countries()
,
gisco_get_lau()
,
gisco_get_nuts()
,
gisco_get_postalcodes()
,
gisco_get_units()
# NOT RUN {
cities <- gisco_get_urban_audit(year = "2020", level = "CITIES")
bcn <- cities[cities$URAU_NAME == "Barcelona", ]
library(ggplot2)
ggplot(bcn) +
geom_sf()
# }
Run the code above in your browser using DataLab