GISCO geodata bulk download

Download zipped data from GISCO to the cache_dir and extract the relevant files.

Usage

gisco_bulk_download(
  id = c("countries", "coastal_lines", "communes", "lau", "nuts", "urban_audit",
    "postal_codes"),
  year = 2016,
  cache_dir = NULL,
  update_cache = FALSE,
  verbose = FALSE,
  resolution = 10,
  ext = c("shp", "geojson", "svg", "json", "gdb"),
  recursive = deprecated(),
  ...
)

Source

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

Arguments

id

A character string or numeric value with the dataset type to download, see Details. Supported values are:

• "countries".

• "coastal_lines".

• "communes".

• "lau".

• "nuts".

• "urban_audit".

• "postal_codes".

  This argument replaces the previous (deprecated) argument id_giscoR.

year

A character string or numeric value with the release year of the file, see Details.

cache_dir

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

update_cache

A logical value indicating whether to refresh the cached file. Defaults to FALSE. When set to TRUE, it forces a new download.

verbose

A logical value. If TRUE displays informational messages.

resolution

A character string or numeric value with the geospatial data resolution. One of:

• "60": 1:60 million.

• "20": 1:20 million.

• "10": 1:10 million.

• "03": 1:3 million.

• "01": 1:1 million.

ext

The extension of the file or files to download. Available formats are "shp", "geojson", "svg", "json" and "gdb". See Details.

recursive

recursive is no longer supported. It will never perform recursive extraction of child .zip files. This is the case for shp.zip inside the top-level .zip, which will not be unzipped.

...

Ignored. The argument id_giscoR () is captured via ... and redirected to id with a warning.

Value

An invisible character vector with the full path of the files extracted. See Examples.

Details

Some arguments only apply to a specific value of "id". For example "resolution" is ignored for values "communes", "lau", "urban_audit" and "postal_codes".

See available years in the corresponding functions:

• gisco_get_countries().

• gisco_get_coastal_lines().

• gisco_get_communes().

• gisco_get_lau().

• gisco_get_nuts().

• gisco_get_urban_audit().

• gisco_get_postal_codes().

The usual extensions used across giscoR are "gpkg" and "shp", but other formats are already available on GISCO. After a bulk download, you may need to adjust the default ext value in the corresponding function to connect it with the downloaded files (see Examples).

See also

Single-unit and additional download utilities: gisco_get_unit

Examples

tmp <- file.path(tempdir(), "testexample")
# \donttest{
dest_files <- gisco_bulk_download(
  id = "countries", resolution = 60,
  year = 2024, ext = "geojson",
  cache_dir = tmp
)
# Read one file.
library(sf)
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.4.0; sf_use_s2() is TRUE
read_sf(dest_files[1]) |> head()
#> Simple feature collection with 6 features and 13 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 2110342 ymin: -3415366 xmax: 13761830 ymax: 2744026
#> Projected CRS: ETRS89-extended / LAEA Europe
#> # A tibble: 6 × 14
#>   CNTR_ID COUNTRY_URI CNTR_NAME      NAME_ENGL NAME_FREN ISO3_CODE SVRG_UN CAPT 
#>   <chr>   <chr>       <chr>          <chr>     <chr>     <chr>     <chr>   <chr>
#> 1 CC      CCK         Cocos Keeling… Cocos (K… Îles des… CCK       AU Ter… West…
#> 2 CD      COD         République Dé… Democrat… Républiq… COD       UN Mem… Kins…
#> 3 CF      CAF         République Ce… Central … Républiq… CAF       UN Mem… Bang…
#> 4 CG      COG         Congo-Kongo-K… Congo     Congo     COG       UN Mem… Braz…
#> 5 CH      CHE         Schweiz-Suiss… Switzerl… Suisse    CHE       UN Mem… Bern 
#> 6 CI      CIV         Côte D’Ivoire  Côte D’I… Côte d’I… CIV       UN Mem… Yamo…
#> # ℹ 6 more variables: STAT_CODE <chr>, EU_STAT <chr>, EFTA_STAT <chr>,
#> #   CC_STAT <chr>, NAME_GERM <chr>, geometry <MULTIPOLYGON [m]>

# Connect the function with the downloaded data.

connect <- gisco_get_countries(
  resolution = 60,
  year = 2024, ext = "geojson",
  cache_dir = tmp, verbose = TRUE
)
#> ℹ Cache directory is /tmp/RtmpoKLIXl/testexample/countries.
#> ✔ File already cached: /tmp/RtmpoKLIXl/testexample/countries/CNTR_RG_60M_2024_4326.geojson.

# The message shows that the file is already cached.
# }
# Clean up.
unlink(tmp, force = TRUE)