Skip to contents

GISCO API single download

Source: R/gisco-get-unit-country.R, R/gisco-get-unit-nuts.R, R/gisco-get-unit-urban-audit.R
gisco_get_unit.Rd

Download datasets of single spatial units from GISCO to the cache_dir.

Unlike gisco_get_countries(), gisco_get_nuts() or gisco_get_urban_audit() (that downloads a full dataset and applies filters), these functions download a single per unit, reducing the time of downloading and reading into your R session.

Usage

gisco_get_unit_country(
  unit = "ES",
  year = 2024,
  epsg = c(4326, 3857, 3035),
  cache = TRUE,
  update_cache = FALSE,
  cache_dir = NULL,
  verbose = FALSE,
  resolution = c(1, 3, 10, 20, 60),
  spatialtype = c("RG", "LB")
)

gisco_get_unit_nuts(
  unit = "ES416",
  year = 2024,
  epsg = c(4326, 3857, 3035),
  cache = TRUE,
  update_cache = FALSE,
  cache_dir = NULL,
  verbose = FALSE,
  resolution = c(1, 3, 10, 20, 60),
  spatialtype = c("RG", "LB")
)

gisco_get_unit_urban_audit(
  unit = "ES001F",
  year = 2021,
  epsg = c(4326, 3857, 3035),
  cache = TRUE,
  update_cache = FALSE,
  cache_dir = NULL,
  verbose = FALSE,
  spatialtype = c("RG", "LB")
)

Source

https://gisco-services.ec.europa.eu/distribution/v2/

All the source files are .geojson files.

Arguments

unit

character vector of unit ids to be downloaded. See Details.

year

character string or number. Release year of the file.

epsg

character string or number. Projection of the map: 4-digit EPSG code. One of:

cache

logical. Whether to do caching. Default is TRUE. See Caching strategies section in gisco_set_cache_dir().

update_cache

logical. Should the cached file be refreshed?. Default is FALSE. When set to TRUE it would force a new download.

cache_dir

character string. A path to a cache directory. See Caching strategies section in gisco_set_cache_dir().

verbose

logical. If TRUE displays informational messages.

resolution

character string or number. Resolution of the geospatial data. One of:

  • "60": 1:60 million.

  • "20": 1:20 million.

  • "10": 1:10 million.

  • "03": 1:3 million.

  • "01": 1:1 million.

spatialtype

character string. Type of geometry to be returned. Options available are:

  • "RG": Regions - MULTIPOLYGON/POLYGON object.

  • "LB": Labels - POINT object.

Value

A sf object.

Details

Check the available unit ids with the required combination of arguments with gisco_get_metadata().

Note

Please check the download and usage provisions on gisco_attributions().

See also

gisco_get_metadata(), gisco_get_countries(), gisco_get_nuts(), gisco_get_urban_audit().

Additional utils for downloading datasets: gisco_bulk_download()

Examples

# Get metadata
cities <- gisco_get_metadata("urban_audit", 2020)


# Valencia, Spain
valencia <- cities[grep("Valencia", cities$URAU_NAME), ]
valencia
#> # A tibble: 3 × 10
#>   URAU_CODE URAU_CATG CNTR_CODE URAU_NAME CITY_CPTL CITY_KERN FUA_CODE 
#>   <chr>     <chr>     <chr>     <chr>     <chr>     <chr>     <chr>    
#> 1 ES003L3   F         ES        Valencia  ""        ""        ""       
#> 2 ES003C1   C         ES        Valencia  ""        "ES003K1" "ES003L3"
#> 3 ES003K1   K         ES        Valencia  ""        ""        ""       
#> # ℹ 3 more variables: NUTS3_2016 <chr>, AREA_SQM <dbl>, NUTS3_2021 <chr>
library(dplyr)
# Now get the shapes and order by AREA_SQM
valencia_sf <- gisco_get_unit_urban_audit(
  unit = valencia$URAU_CODE,
  year = "2020",
) |>
  arrange(desc(AREA_SQM))
# Plot
library(ggplot2)

ggplot(valencia_sf) +
  geom_sf(aes(fill = URAU_CATG)) +
  scale_fill_viridis_d() +
  labs(
    title = "Valencia",
    subtitle = "Urban Audit 2020",
    fill = "Category"
  )