Help for package ffm

Type:

Package

Title:

Download Official Spatial Data from Germany

Version:

0.1.1

Description:

Provides quick and easy access to official spatial data from Germany’s Federal Agency for Cartography and Geodesy (BKG) https://gdz.bkg.bund.de/. Interfaces various web feature services (WFS) and download servers. Allows retrieval, caching and filtering with a wide range of open geodata products, including administrative or non-administrative boundaries, land cover, elevation models, geographic names, and points of interest covering Germany. Can be particularly useful for linking regional statistics to their spatial representations and streamlining workflows that involve spatial data of Germany.

License:

MIT + file LICENSE

Encoding:

UTF-8

LazyData:

true

RoxygenNote:

7.3.2

Depends:

R (≥ 3.5)

Imports:

cli, rlang, zip, httr2, xml2, sf

Suggests:

tibble, terra, arrow, ggplot2, knitr, rmarkdown, testthat (≥ 3.2.2)

Config/testthat/edition:

VignetteBuilder:

knitr

NeedsCompilation:

Packaged:

2025-11-05 15:00:25 UTC; PC

Author:

Jonas Lieth

[aut, cre, cph]

Maintainer:

Jonas Lieth <jonas.lieth@gesis.org>

Repository:

CRAN

Date/Publication:

2025-11-09 16:10:09 UTC

German administrative boundaries

Description

Three sf dataframes containing all geometries of German districts, federal states, and the country, respectively. The reference year is 2023.

Usage

bkg_krs

bkg_states

bkg_germany

Format

For the dataframe format, see bkg_admin.

An object of class sf (inherits from tbl_df, tbl, data.frame) with 25 rows and 25 columns.

An object of class sf (inherits from tbl_df, tbl, data.frame) with 7 rows and 25 columns.

Source

Examples

bkg_krs

Administrative areas

Description

Retrieve polygon geometries of administrative areas in Germany. All administrative levels are supported at different spatial resolutions.

bkg_admin interfaces a WFS that allows prefiltering but provides no historical data and allows a maximum scale of 1:250,000.
bkg_admin_archive allows access to historical data but has no prefiltering.
bkg_admin_highres (vg25) allows access to high-resolution data going as low as 1:25,000 but allows no prefiltering.

These functions interface the vg* products of the BKG.

Usage

bkg_admin(
  ...,
  level = "krs",
  scale = c("250", "1000", "2500", "5000"),
  key_date = c("0101", "1231"),
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

bkg_admin_archive(
  level = "krs",
  scale = c("250", "1000", "2500", "5000"),
  key_date = c("0101", "1231"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_admin_highres(
  level = "krs",
  year = "latest",
  layer = NULL,
  timeout = 600,
  update_cache = FALSE
)

Arguments

...

Used to construct CQL filters. Dot arguments accept an R-like syntax that is converted to CQL queries internally. These queries basically consist of a property name on the left, an aribtrary vector on the right, and an operator that links both sides. If multiple queries are provided, they will be chained with AND. The following operators and their respective equivalents in CQL and XML are supported:

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

To construct more complex queries, you can use the filter argument to pass CQL queries directly. Also note that you can switch between CQL and XML queries using options(ffm_query_language = "xml"). See also wfs_filter.

level

Administrative level to download. Must be one of "sta" (Germany), "lan" (federal states), "rbz" (governmental districts), "krs" (districts), "vwg" (administrative associations), "gem" (municipalities), "li" (boundary lines), or "pk" (municipality centroids). Defaults to districts.

scale

Scale of the geometries. Can be "250" (1:250,000), "1000" (1:1,000,000), "2500" (1:2,500,000) or "5000" (1:5,000,000). If "250", population data is included in the output. Defaults to "250".

key_date

For resolution %in% c("250", "5000"), specifies the key date from which to download administrative data. Can be either "0101" (January 1) or "1231" (December 31). The latter is able to georeference statistical data while the first integrates changes made in the new year. If "1231", population data is attached, otherwise not. Note that population data is not available at all scales (usually 250 and 1000). Defaults to "0101".

bbox

An sf geometry or a boundary box vector of the format c(xmin, ymin, xmax, ymax). Used as a geometric filter to include only those geometries that relate to bbox according to the predicate specified in predicate. If an sf geometry is provided, coordinates are automatically transformed to ESPG:25832 (the default CRS), otherwise they are expected to be in EPSG:25832.

poly

An sf geometry. Used as a geometric filter to include only those geometries that relate to poly according to the predicate specified in predicate. Coordinates are automatically transformed to ESPG:25832 (the default CRS).

predicate

A spatial predicate that is used to relate the output geometries with the object specified in bbox or poly. For example, if predicate = "within", and bbox is specified, returns only those geometries that lie within bbox. Can be one of "equals", "disjoint", "intersects", "touches", "crosses", "within", "contains", "overlaps", "relate", "dwithin", or "beyond". Defaults to "intersects".

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

An EPSG code specifying a coordinate reference system of the output. If you're unsure what this means, try running sf::st_crs(...)$epsg on a spatial object that you are working with. Defaults to 3035.

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

year

Version year of the dataset. You can use latest to retrieve the latest dataset version available on the BKG's geodata center. Older versions can be browsed using the archive.

timeout

Timeout value for the data download passed to req_timeout. Adjust this if your internet connection is slow or you are downloading larger datasets.

update_cache

By default, downloaded files are cached in the tempdir() directory of R. When downloading the same data again, the data is not downloaded but instead taken from the cache. Sometimes this can be not the desired behavior. If you want to overwrite the cache, pass TRUE. Defaults to FALSE, i.e. always adopt the cache if possible.

layer

The vg25 product used in bkg_admin_highres contains a couple of metadata files. You can set a layer name to read these files, otherwise the main file is read.

Value

An sf dataframe with multipolygon geometries and different columns depending on the geometry type. Areal geometries generally have the following columns:

objid: Unique object identifier
beginn: Creation of the object in the DLM
ade: Integer representing the administrative level. Can be one of
- 1: Germany
- 2: Federal state
- 3: Governmental district
- 4: District
- 5: Administrative association
- 6: Municipality
gf: Integer representing the geofactor; whether an area is "structured" or not. Land is structured if it is part of a state or other administrative unit but is not further divided into administrative units. Can be one of
- 1: Unstructured, waterbody
- 2: Structured, waterbody
- 3: Unstructured, land
- 4: Structured, land
bsg: Special areas, can be 1 (Germany) or 9 (Lake Constance)
ars: Territorial code (Amtlicher Regionalschlüssel). The ARS is stuctured hierarchically as follows:
- Position 1-2: Federal state
- Position 3: Government region
- Position 4-5: District
- Position 6-9: Administrative association
- Position 10-12: Municipality
ags: Official municipality key (Amtlicher Gemeindeschlüssel). Related to the ARS but shortened to omit position 6 to 9. Structured as follows:
- Position 1-2: Federal state
- Position 3: Government region
- Position 4-5: District
- Position 6-8: Municipality
sdv_ars: ARS of the seat of administration
gen: Geographical name
bez: Label of the administrative unit
ibz: Identifier of the label
bem: Comment on the label
nbd: Formation of the geographical name. Can be "ja" if the label is part of the name or "nein" otherwise.
nuts: NUTS identifier based on the Eurostat regional classification
ars_0: ARS identifier with trailing zeroes
ags_0: AGS identifier with trailing zeroes
wsk: Legally relevant date for the effectiveness of administrative changes
sn_l: Federal state component of the ARS
sn_r: Governmental district component of the ARS
sn_k: District component of the ARS
sn_v1: First part of the administrative association component of the ARS
sn_v2: Second part of the administrative association component of the ARS
sn_g: Municipality component of the ARS
fk_3: Purpose of the third key position. If "R", indicates the government region, if "K", indicates the district
dkm_id: Identifier in the digital landscape model (DLM250)
ewz: Number of inhabitants
kfl: Land register area in square kilometers

Boundary geometries ("li") can have additional columns:

agz: Type of border. Can be one of
- 1: National border
- 2: State border
- 3: Governmental district border
- 4: District border
- 5: Administrative association border
- 6: Municipality border
- 9: Coastline
rdg: Legal definition of a border. Can be 1 (determined), 2 (not determined) or 9 (coastline)
gm5: Border characteristic of administrative association borders (AGZ 5). Used to describe the purpose of these borders. Can be 0 (characteristics by AGZ) or 8 (non-association border)
gmk: Border characteristic by coast/ocean. Specifies whether a border runs a long a waterbody. Can be one of
- 7: borders on the ocean
- 8: auxiliary borders on the ocean
- 9: borders at the coastline
- 0: no characteristics
dlm_id: Identifier in the digital landscape model (DLM250)

Point geometries ("pk") have the following additional columns:

otl: Name of the locality in the digital landscale model (DLM250)
lon_dez: Decimal longitude
lat_dez: Decimal latitude
lon_gms: Geographical longitude
lat_gms: Geographical latitude

Query language

By default, WFS requests use CQL (Contextual Query Language) queries for simplicity. CQL queries only work together with GET requests. This means that when the URL is longer than 2048 characters, they fail. While POST requests are much more flexible and able to accommodate long queries, XML is really a pain to work with and I'm not confident in my approach to construct XML queries. You can control whether to send GET or POST requests by setting options(ffm_query_language = "XML") or options(ffm_query_language = "CQL").

Examples


# You can use R-like operators to query the WFS
bkg_admin(ags %LIKE% "05%") # districts in NRW
bkg_admin(sn_l == "05") # does the same thing
bkg_admin(gen %LIKE% "Ber%") # districts starting with Ber*

# To query population and area, the key date must be December 31
bkg_admin(ewz > 500000, key_date = "1231") # districts over 500k people
bkg_admin(kfl <= 100, key_date = "1231") # districts with low land register area

# Using `gf == 9`, you can exclude waterbodies like oceans
states <- bkg_admin(scale = "5000", level = "lan", gf == 9)
plot(states$geometry)

# Download historical data
bkg_admin_archive(scale = "5000", level = "sta", year = "2021")


# Download high-resolution data (takes a long time!)
bkg_admin_highres(level = "lan")

Administrative hierarchy

Description

Retrieve polygon geometries of municipalities in Germany with details on their relationships to administrative areas of higher levels in the territorial hierarchy. The output of this functions contains the identifiers and names of the NUTS1 to NUTS3 areas that each municipality belongs to.

Usage

bkg_admin_hierarchy(
  key_date = c("0101", "1231"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

Arguments

key_date

year

Version year of the dataset. You can use latest to retrieve the latest dataset version available on the BKG's geodata center. Older versions can be browsed using the archive.

timeout

Timeout value for the data download passed to req_timeout. Adjust this if your internet connection is slow or you are downloading larger datasets.

update_cache

Value

An sf tibble with multipolygon geometries similar to the output of bkg_admin(level = "gem"). The tibble additionally contains columns NUTS*_CODE and NUTS*_NAME giving the identifiers and names of the administrative areas the municipalities belong to.

Examples


bkg_admin_hierarchy()

Official keys

Description

Retrieve geographical names associated with official municipality keys and regional keys. To retrieve their polygon geometries, see bkg_admin.

These functions interface the wfs_gnde product of the BKG.

Usage

bkg_ags(..., filter = NULL, properties = NULL, max = NULL)

bkg_ars(..., filter = NULL, properties = NULL, max = NULL)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe containing the respective identifier and geographical names related to their state, government region, district and municipality. bkg_ars additionally returns the name of the administrative association.

Query language

While other WFS interfaces like bkg_admin allow querying using CQL or XML, bkg_ags and bkg_ars (using the GNDE service) ONLY support XML. This has implications for the allowed query filters (see wfs_filter).

Examples


# Either get geographical names for identifiers
bkg_ars(ars == "01")

# ... or identifiers for geographical names
bkg_ars(gemeinde == "Köln")

Airports

Description

Retrieve international, regional, and special airports in Germany. Small landing sites are not included.

These functions interface the wfs_poi_open product of the BKG.

Usage

bkg_airports(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe containing the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
poi_id: Unique primary key of a point of interest
icao_code: ICAO code of the airport
typ: Type of airport. Can be one of the following:
- international: International airport
- regional: Regional airport
- Sonderflughafen: Special airport

Query language

Examples


# Get all airports in NRW
airports <- bkg_airports(ars %LIKE% "05%")
nrw <- bkg_admin(level = "lan", sn_l == "05")
plot(nrw$geometry)
plot(airports$geometry, add = TRUE, pch = 16)

Area code regions

Description

Retrieves area code regions (Vorwahlgebiete) in Germany. Area code regions are based on the number of registered telephone numbers.

Usage

bkg_area_codes(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

max

Maximum number of results to return.

Value

An sf dataframe containing polygon geometries and the area code (vorwahl) associated with the region.

Query language

While other WFS interfaces like bkg_admin allow querying using CQL or XML, bkg_area_codes ONLY supports XML. This has implications for the allowed query filters (see wfs_filter).

Examples


vorwahlen <- bkg_area_codes(vorwahl %LIKE% "0215%")
plot(vorwahlen$geometry)

Regions of authority

Description

Retrieve regions of administrative responsibility for job centers, employment agencies, offices of employment agencies, regional directorates of the Federal Employment Agency as well as local, regional, and higher regional courts.

This function interfaces the wfs_bzb-open product of the BKG.

Usage

bkg_authorities(
  authority,
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

authority

Type of authority for which to retrieve regions of responsibility. Must be one of "employment_agencies", "employment_offices", "job_centers", "directorates", "local_courts", "regional_courts", or "higher_regional_courts".

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

An sf tibble with multipolygon geometries and the following columns:

id: Identifier of the authority region
dst_id: Identifier of the authority office
uebergeord: Name of the superior authority
name: Name of the authority

Query language

Examples


# Get only local courts that are subordinates of the regional court Cottbus
bkg_authorities(
  authority = "local_courts",
  uebergeord %LIKE% "%Cottbus",
  uebergeord %LIKE% "Landgericht%"
)

Corine Land Cover

Description

Retrieve land cover polygons in Germany based on the Corine Land Cover (CLC) nomenclature. Corine Land Cover is a way to project by the European Commission to consistenly classify both land cover and land use.

This function interfaces the wfs_clc5_* products of the BKG.

Usage

bkg_clc(
  ...,
  year = "2018",
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

year

Version year of the dataset. You can use latest to retrieve the latest dataset version available on the BKG's geodata center. Older versions can be browsed using the archive.

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

An sf dataframe with polygon geometries and the following columns:

clc*: CLC land cover classes for the given year. An overview of all CLC classes can be found in the Copernicus documentation.
shape_length: Circumference of the polygon in meters
shape_area: Area of the polygon in square meters

Query language

Examples


# Get glaciers in Germany
bkg_clc(clc18 == "335")

# Get all coastal wetlands
bkg_clc(clc18 %LIKE% "42%")

# Get only wetlands in Lower Saxony
rlang::local_options(ffm_query_language = "xml")
lowsax <- bkg_admin(level = "lan", scale = "5000", sn_l == "03", gf == 9)
wetlands <- bkg_clc(clc18 %LIKE% "4%", poly = lowsax)
plot(lowsax$geometry)
plot(wetlands$geometry, add = TRUE)

Border crossings

Description

Retrieve border crossings in Germany. A road is a border crossing if it touches an international border and it continues on the foreign side. This includes ferry connections but not dirt roads.

Usage

bkg_crossings(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe with the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
ort: Name of the nearest place
strasse: Number or label of the border-crossing street
typ: Type of checkpoint; always "Straßenverkehr"

Query language

Examples


# Get all border crossings in Bavaria
crossings <- bkg_crossings(bundesland == "Bayern")
plot(crossings$geometry, pch = 16)

Digital elevation model

Description

Retrieve the digital elevation model (DEM) for the territory of Germany.

Usage

bkg_dem(bbox = NULL, interpolation = NULL, epsg = 3035)

Arguments

bbox

An sf geometry or a boundary box vector of the format c(xmin, ymin, xmax, ymax). Used as a geometric filter to mask the coverage raster. If an sf geometry is provided, coordinates are automatically transformed to ESPG:25832 (the default CRS), otherwise they are expected to be in EPSG:25832.

interpolation

Interpolation method to preprocess the raster. Can be "nearest-neighbor", "linear", or "cubic". Does not seem to work currently - despite being listed as a capability of the WCS.

epsg

Value

A SpatRaster containing elevation data.

Examples


library(sf)

# Elevation around Hanover
han <- st_sfc(st_point(c(9.738611, 52.374444)), crs = 4326)
han <- st_buffer(st_transform(han, 3035), dist = 2000)
dem <- bkg_dem(bbox = han)
terra::plot(dem)

Digital landscape model (DLM)

Description

Retrieve objects from the digital landscape model (DLM). DLMs are a description of topographical objects of a landscape. Many other services from the BKG are derived from the DLM.

Although this function lets you download each feature type in the DLM, you still need to know about what data is available and what the features in the output actually mean. Since the DLM gets pretty complicated, you are advised to take a look at the GeoInfoDok object type catalog.

This function interfaces the dlm* products of the BKG.

Usage

bkg_dlm(
  type,
  ...,
  shape = c("point", "line", "polygon"),
  scale = c("250", "1000"),
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

type

Feature type of the DLM. Can either be the identifier (e.g., 41010) or its description (e.g., Siedlungsflaeche). The description can either be prefixed with AX_ or not. Providing an identifier directly is generally faster as the description needs to be matched by requesting the GetCapabilities endpoint of the service.

Note that not all feature types are available for all shapes (see the shape argument). To see all available feature types, you can run bkg_feature_types("dlm250") or bkg_feature_types("dlm1000").

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

shape

Geometry type of the feature type. Must be one of "point", "line", or "polygon". Defaults to "point". Not all shapes are available for all feature types.

scale

Scale of the geometries. Can be "250" (1:250,000) or "1000" (1:1,000,000). Defaults to "250".

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

An sf tibble with the geometry suggested by shape. The columns can vary depending of the selected feature type. The meanings of the columns can also change depending on the feature type. Check out the GeoInfoDok object type catalog for a detailed documentation of the DLM metadata. Some more general columns are included for all feature types; these include:

id: Identifier of an object
land: ISO-2 code of the country, usually DE
modellart: Model type
objart: Feature type of the digital landscape model (DLM)
objart_txt: Title of the feature type
objid: Unique object identifier
beginn: Creation of the object in the DLM
ende: Deletion of the object from the DLM
objart_z: Object type of the composite object (ZUSO)
objid_z: Object type of the composite object (ZUSO)

Query language

Examples


# Retrieve all train tracks in Leipzig
library(sf)
lzg <- st_sfc(st_point(c(12.37475, 51.340333)), crs = 4326)
lzg <- st_buffer(st_transform(lzg, 3035), dist = 10000, endCapStyle = "SQUARE")

tracks <- bkg_dlm("Bahnstrecke", shape = "line", poly = lzg)
tracks

plot(lzg)
plot(tracks$geometry, add = TRUE)

# Filter all tracks that are not rail cargo
bkg_dlm("Bahnstrecke", shape = "line", poly = lzg, bkt == "1102")

# Directly providing the identifier is faster
bkg_dlm("42014", shape = "line", poly = lzg)

Geographical objects and endonyms

Description

Get geographic names including toponyms and endonyms. bkg_geonames retrieves the geographical "objects" based on the digital landscape model (DLM). These objects contain a set of metadata and a national name identifier (NNID). These NNIDs can be used to join with the endonyms related to a geographical object (bkg_endonyms).

These functions interface the wfs_gnde product of the BKG.

Usage

bkg_geonames(
  ...,
  names = TRUE,
  ags = FALSE,
  dlm = FALSE,
  status = FALSE,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

bkg_endonyms(..., filter = NULL, properties = NULL, max = NULL)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

names

If TRUE, includes endonyms of the geographical objects in the output using bkg_endonyms. Technically, this can be FALSE, because the endpoint only returns meta data on geographical names by default. If this argument is TRUE, the output is merged with the endonym table requiring an additional request. Defaults to TRUE.

ags

If TRUE, resolves AGS codes to geographical names using bkg_ags. Note that setting this to TRUE requires an additional web request. Defaults to FALSE.

dlm

If TRUE, adds the DLM identifier corresponding to the national name identifiers (NNID) of the output using bkg_dlm. Note that setting this to TRUE requires an additional web request. Defaults to FALSE.

status

If TRUE, adds the date of the objects last edit to the output. Note that setting this to TRUE requires an additional web request. Defaults to FALSE.

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Details

These functions make use of the GN-DE WFS, just like bkg_ags, bkg_ars, and bkg_area_codes. The infrastructure behind it is actually quite sophisticated and this function may not live up to these standards. You can use bkg_feature_types and bkg_wfs to manually explore the service's endpoints if required.

Value

A dataframe containing the following columns:

nnid: National name identifier
landesCode: Country identifier; 276 is Germany.
beschreibung: Optional details
geoLaenge: Geographical longitude
geoBreite: Geographical latitude
hoehe: Elevation above sea level
hoeheger: Computed elevation above sea level
groesse: Undocumented, but I guess this relates to the suggested print size of the labels
ewz: Number of inhabitants
ewzger: Computed number of inhabitants
ags: Official municipality key (Amtlicher Gemeindeschlüssel). Related to the ARS but shortened to omit position 6 to 9. Structured as follows:
- Position 1-2: Federal state
- Position 3: Government region
- Position 4-5: District
- Position 6-8: Municipality
gemteil: Whether the place is part of a municipality
virtuell: Whether the place is a real or virtual locality
ars: Territorial code (Amtlicher Regionalschlüssel). The ARS is stuctured hierarchically as follows:
- Position 1-2: Federal state
- Position 3: Government region
- Position 4-5: District
- Position 6-9: Administrative association
- Position 10-12: Municipality

If ags = TRUE, adds the output of bkg_ags. If dlm = TRUE, adds a column dlm_id containing identifiers of bkg_dlm.

bkg_endonyms contains the following columns:

name: Name of the geographical object
geschlecht: If applicable, the grammatical gender of a geographical name

These are also included in the output of bkg_geonames if names = TRUE.

Query language

While other WFS interfaces like bkg_admin allow querying using CQL or XML, bkg_geonames and bkg_endonyms (using the GNDE service) ONLY support XML. This has implications for the allowed query filters (see wfs_filter).

Examples


# Plot geographical objects in Cologne
library(sf)
library(ggplot2)
cgn <- st_sfc(st_point(c(6.956944, 50.938056)), crs = 4326)
cgn <- st_buffer(st_transform(cgn, 3035), dist = 500)

cgn_names <- bkg_geonames(poly = cgn)
st_geometry(cgn_names) <- st_centroid(st_geometry(cgn_names))
cgn_names <- cgn_names[lengths(st_intersects(cgn_names, cgn)) > 0, ]
ggplot(cgn_names) + geom_sf_text(aes(label = name)) + theme_void()

INSPIRE grids

Description

Retrieve geometries of INSPIRE-compliant grid geometries (also called "GeoGitter"). bkg_grid_fast() is much faster than bkg_grid_full() by downloading heavily compressed versions grids. This happens at the cost of data richness as bkg_grid_fast() only contains the geometries and nothing else. Note that the arrow package needs to be installed to use bkg_grid_fast().

Note that the output contains point geometries. Most of the times, you want to work with rasters instead. To convert a given object out, type the following (terra package required):

terra::rast(out)

These functions interface the GeoGitter product of the BKG.

Usage

bkg_grid_fast(
  year = c("2019", "2018", "2017", "2015"),
  resolution = c("100km", "10km", "5km", "1km", "250m", "100m"),
  timeout = 600,
  update_cache = FALSE
)

bkg_grid_full(
  year = "latest",
  resolution = c("100km", "10km", "5km", "1km", "250m", "100m"),
  timeout = 600,
  update_cache = FALSE
)

Arguments

year

Version of the grid. Can be "2015", "2017", "2018" or "2019". For bkg_grid_fast, "latest" downloads the latest version of the grid.

resolution

Cell size of the grid. Can be "100m", "250m", "1km", "5km", "10km", or "100km".

timeout

Timeout value for the data download passed to req_timeout. Adjust this if your internet connection is slow or you are downloading larger datasets.

update_cache

Details

The following table gives a rough idea of how much less data bkg_grid_fast needs to download for each resolution compared to bkg_grid_full.

Size	fast	full
100km	0.78 kB	933 kB
10km	2.68 kB	1,015 kB
5km	3.53 kB	1,253 kB
1km	28.7 kB	5,249 kB
500m	133 kB	15,902 kB
250m	289 kB	53,900 kB
100m	1,420 kB	291,000 kB

Value

bkg_grid_fast returns an sf dataframe with point geometries and no features. bkg_grid_full also returns point geometries but with the following additional features:

x_sw: X coordinate of the South-West corner of a grid cell
y_sw: Y coordinate of the South-West corner of a grid cell
f_staat: State area in the grid cell in square meters
f_land: Land area in the grid cell in square meters
f_wasser: Water area in the grid cell in square meters
p_staat: Share of state area in the grid cell
p_land: Share of land area in the grid cell
p_wasser: Share of water area in the grid cell
ags: Official municipality key (Amtlicher Gemeindeschlüssel). Related to the ARS but shortened to omit position 6 to 9. Structured as follows:
- Position 1-2: Federal state
- Position 3: Government region
- Position 4-5: District
- Position 6-8: Municipality

Note that ags is only included for resolutions "100m" and "250m"

Examples


# Return a bare-bones version of the INSPIRE grid
grid <- bkg_grid_fast(year = "2019", resolution = "100km")

# Return a fully detailed version instead
grid_full <- bkg_grid_full(resolution = "5km")

plot(grid)

# Convert grid to SpatRaster
if (requireNamespace("terra")) {
  library(terra)
  raster <- rast(vect(grid_full["p_wasser"]), type = "xyz")
  plot(raster, main = "Share of water area")
}

Heliports

Description

Get heliports in Germany. Based on data from third-party providers and image classification of aerial imagery.

Usage

bkg_heliports(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe with the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
code: Identifier of the heliport
name_bkg: Name of the landing site according to BKG
name_dfs: Name of the landing size according to Deutsche Flugsicherung (DFS)
airport_pk: Identifier according to the LFS aviation manual
befestigun: Pavement type of the landing site. Can be:
- befestigt: paved
- teilweise befestigt: partially paved
- unbefestigt: unpaved
kennzeich: Marking of the landing size. Can be:
- gekennzeichnet: marked
- nicht gekennzeichnet: not marked
lage: Location of the landing size. Can be:
- D: Roof
- F: Field
- PG: Platform next to a hospital
- W: Pasture
- LP: Landing site
- PP: Parking lot
- LP / W: Paved landing size on pasture
- F / W: Field or pasture
- LP / Str.: Landing size next to a street
typ: Type of heliport. Can be:
- H: Heliport
- HH: Heliport at a hospital
- MH: Military heliport
typ2: Additional heliport type for landing sites with an air rescue station. Can be:
- HRLS: Helicopter air rescue station
- ITH: Intensive transport helicopter
betreiber: Operator of the heliport
helikopter: Name of the helicopter belonging to the air rescue station
status: Whether the point geometry was edited by the BKG. Can be:
- Original: not edited
- Verschoben: moved
- neu: newly added
quelle: Source of the information. Can be:
- BKG: Own research by the BKG
- DFS-Liste: Provided by DFS
- LBA-Liste: Provided by the Federal Aviation Office (LBA)
- MHW: Provided by the Medical Disaster Relief Organization (MHW)
- RTH.Info: Provided by rth.info

Query language

Examples


# Get only military heliports
bkg_heliports(typ == "MH")

# Get only rooftop heliports
bkg_heliports(lage == "D")

Vehicle registration plates

Description

Retrieve motor vehicle registration plate regions in Germany. Registration plate regions are discerned by their area code (Unterscheidungszeichen) which indicate the place where a vehicle was registered. These regions partially overlap with districts but are not entirely identical.

This function interfaces the wfs_kfz250 product of the BKG.

Usage

bkg_kfz(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

An sf dataframe with multipolygon geometries and the following columns:

debkgid: Identifier in the digital landscape model DLM250
nnid: National name identifier
name: Name of the geographical object
ars: Territorial code (Amtlicher Regionalschlüssel). The ARS is stuctured hierarchically as follows:
- Position 1-2: Federal state
- Position 3: Government region
- Position 4-5: District
- Position 6-9: Administrative association
- Position 10-12: Municipality
oba: Name of the ATKIS object type
kfz: Vehicle registration area code, comma-separated in case of multiple codes
geola: Geographical longitude
geobr: Geographical latitude
gkre: Gauß-Krüger easting
gkho: Gauß-Krüger northing
utmre: UTM easting
utmho: UTM northing

Examples


library(ggplot2)

kfz <- bkg_kfz(ars %LIKE% "053%")
ggplot(kfz) +
  geom_sf(fill = NA) +
  geom_sf_text(aes(label = kfz)) +
  theme_void()

Kilometrage

Description

Get kilometrages of German federal motorways. Kilometrages are markers for each kilometer of a highway. They can be used to create linear referencing systems (LRS).

Usage

bkg_kilometrage(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe containing the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
bez: Label of the federal motorway
kilometer: Kilometrage of the motorway
richtung: Direction of the kilometrage

Query language

Examples


# Get the kilometrage of the A2 motorway
a2 <- bkg_kilometrage(bez == "A2")
plot(a2["kilometer"], pch = 16)

NUTS regions

Description

Retrieve polygons of NUTS regions.

This function interfaces the nuts* products of the BKG.

Usage

bkg_nuts(
  level = c("1", "2", "3"),
  scale = c("250", "1000", "2500", "5000"),
  key_date = c("0101", "1231"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

Arguments

level

NUTS level to download. Can be "1" (federal states), "2" (inconsistent, something between states and government regions), or "3" (districts). Defaults to federal states.

scale

key_date

year

Version year of the dataset. You can use latest to retrieve the latest dataset version available on the BKG's geodata center. Older versions can be browsed using the archive.

timeout

Timeout value for the data download passed to req_timeout. Adjust this if your internet connection is slow or you are downloading larger datasets.

update_cache

Value

An sf dataframe with multipolygon geometries and the following columns:

GF: Integer representing the geofactor; whether an area is "structured" or not. Land is structured if it is part of a state or other administrative unit but is not further divided into administrative units. Can be one of
- 1: Unstructured, waterbody
- 2: Structured, waterbody
- 3: Unstructured, land
- 4: Structured, land
NUTS_LEVEL: NUTS level. Can be one of
- 1: NUTS-1; federal states
- 2: NUTS-2; inconsistent, somewhere between government regions and federal states
- 3: NUTS-3; districts
NUTS_CODE: Hierarchical key of the NUTS region. Can have a different number of characters depending on the NUTS level:
- NUTS-1: three digits
- NUTS-2: four digits
- NUTS-3: five digits
NUTS_NAME: Geographical name of the NUTS region

Note

This function does not query a WFS so you are only able to download entire datasets without the ability to filter beforehand.

Examples


# Download NUTS state data from 2020
bkg_nuts(scale = "5000", year = 2020)

# Download the latest NUTS district data
bkg_nuts(level = "3")

Quasigeoid

Description

Retrieves the "German Combined Quasigeoid", the official height reference surface of the German land survey above the reference ellipsoid (GRS80).

A quasigeoid is an approximation of the geoid surface used to define normal heights above the earth's surface that is based on more practical assumptions than a true geoid. It defines heights in meters that can be more meaningful than ellipsoidal heights in many applications like surveying, hydrological modeling, engineering, or spatial analysis.

This function interfaces the quasigeoid product of the BKG.

Usage

bkg_quasigeoid(
  year = "latest",
  region = c("all", "coast", "no", "nw", "s", "w"),
  timeout = 120,
  update_cache = FALSE
)

Arguments

year

Version year of the dataset. You can use latest to retrieve the latest dataset version available on the BKG's geodata center. Older versions can be browsed using the archive.

region

Subterritory of Germany. "all" returns the data for all of Germany, "coast" returns only coastal regions and "no", "nw", "s" and "w" refer to cardinal directions. Defaults to "all".

timeout

Timeout value for the data download passed to req_timeout. Adjust this if your internet connection is slow or you are downloading larger datasets.

update_cache

Value

A SpatRaster containing normal heights for the specified region. The data comes in EPSG:4258 and a resolution of 30" x 45" (approximately 0.9 x 0.9 km).

Examples


library(terra)
qgeoid <- bkg_quasigeoid(region = "no")
terra::plot(qgeoid)

Non-administrative regions

Description

Retrieve areal data related to what the BKG calls non-administrative regions. This includes:

bkg_ror: Raumordnungsregionen (Spatial planning regions)
bkg_rg: Reisegebiete (Travel areas)
bkg_amr: Arbeitsmarktregionen (Labor market regions)
bkg_bkr: Braunkohlereviere (Lignite regions)
bkg_krg: Kreisregionen (District regions)
bkg_mbe: BBSR Mittelbereiche (BBSR middle areas)
bkg_ggr: Großstadtregionen (City regions)
bkg_kmr: Metropolregionen (Metropolitan regions)
bkg_mkro: Verdichtungsräume (Conurbations)

These functions interface the ge* product of the BKG.

Usage

bkg_ror(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_rg(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_amr(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_bkr(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_krg(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_mbe(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_ggr(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_kmr(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

bkg_mkro(
  scale = c("250", "1000", "2500", "5000"),
  year = "latest",
  timeout = 120,
  update_cache = FALSE
)

Arguments

scale

year

Version year of the dataset. You can use latest to retrieve the latest dataset version available on the BKG's geodata center. Older versions can be browsed using the archive.

timeout

Timeout value for the data download passed to req_timeout. Adjust this if your internet connection is slow or you are downloading larger datasets.

update_cache

Value

An sf tibble with multipolygon geometries and two features, a regional identifier and the region endonyms.

Seaports

Description

Retrieve seaports to the North and Baltic Sea in Northern Germany.

Usage

bkg_seaports(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe containing the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
poi_id: Unique primary key of a point of interest
betreiber: Operator of the seaport
homepage: Homepage of the operator
typ: Type of seaport. Can be "Seehafen" (seaport) or "See- und Binnenhafen" (sea and inland port)
art: Type of seaport by freight. Can be:
- Güter: Goods
- Güter und Passagiere: Goods and passengers
- Passagiere: Passengers
quelle: Source of the information. Can be:
- BSH: Federal Maritime and Hydrographic Agency
- MarWiLo: Maritime Wirtschaft & Logistik
- ZDS-Seehäfen: Zentralverband der deutschen Seehafenbetriebe

Query language

Examples


# Get only seaports that co-function as inland ports
ports <- bkg_seaports(typ == "See- und Binnenhafen")
germany <- bkg_admin(level = "sta", scale = "5000", gf == 9)
plot(germany$geometry)
plot(ports$geometry, add = TRUE)

Stations and stops

Description

Retrieve data on public transport stations and stops in Germany. Stations and stops are hierarchical. This means that stations represent the structural facilities as hierarchically superior objects and stops are hierarchically inferiors parts of a station (e.g., a single platform at a bus stop).

Usage

bkg_stations(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe with the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
stop_id: Identifier of the station or stop
parent_st: Identifier of the parent station if applicable
verkehrsm: Vehicle used at the station, comma-separated and sorted alphabetically
art: Hierarchical position of a station. Can be:
- Station: A physical structure and hierarchically superior
- Haltestelle: Part of a structure and hierarchically inferior
tag_f_awo: Mean departures per day in a work week
tag_f_wo: Mean departures per day in a full week

Query language

Examples


# Get all long-distance train stations
bkg_stations(verkehrsm %LIKE% "%Fernzug%", art == "Station")

# Get all platforms of long-distance train stations
bkg_stations(verkehrsm %LIKE% "%Fernzug%", art == "Haltestelle")

# Get all stops with high traffic
bkg_stations(tag_f_awo > 1000, art == "Station")

# Get all bus stops with low traffic
bkg_stations(tag_f_awo < 1, verkehrsm %LIKE% "%Bus%", art == "Station")

Trauma centers

Description

Retrieve data on trauma centers in Germany. A trauma center is a hospital certified by the German Society for Trauma Surgery (DGU) that is able to provide maximum care for heavily injured people. Trauma centers are organized in a hierarchical regional network that ranges from local to transregional centers.

Usage

bkg_trauma_centers(
  ...,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  filter = NULL,
  epsg = 3035,
  properties = NULL,
  max = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

bbox

poly

predicate

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

epsg

properties

Vector of columns to include in the output.

max

Maximum number of results to return.

Value

A dataframe containing the following columns:

name: Geographical name of the POI
gemeinde: Municipality name
verwaltung: Administrative association name
kreis: District name
regierungs: Government region name
bundesland: Federal state name
poi_id: Unique primary key of a point of interest
tz_nummer: Unique primary key of the trauma center
strasse: Street
hn: House number
plz: Zip code
ort: Place name
netwerk: Name of the regional trauma center network
abteilung: Name of the medical department
typ: Type of trauma center. Can be:
- LTZ: local trauma center
- RTZ: regional trauma center
- ÜTZ: transregional trauma center

Query language

Examples


# Get only trauma centers specializing on orthopedics
bkg_trauma_centers(abteilung %LIKE% "%orthopäd%")

# Get only local trauma centers
bkg_trauma_centers(typ == "LTZ")

if (requireNamespace("ggplot2")) {
  library(ggplot2)
  centers <- bkg_trauma_centers()
  ggplot() +
  geom_sf(
    data = centers[centers$typ %in% "LTZ",],
    size = 1,
    color = "lightblue1"
  ) +
  geom_sf(
    data = centers[centers$typ %in% "RTZ",],
    size = 2,
    color = "lightblue3"
  ) +
  geom_sf(
    data = centers[centers$typ %in% "ÜTZ",],
    size = 3,
    color = "lightblue4"
  ) +
  theme_void()
}

BKG WCS

Description

Low-level interface to BKG-style web coverage services (WCS). This function is used in all high-level functions of ffm that depend on a WCS, e.g., bkg_dem.

Usage

bkg_wcs(
  coverage_id,
  endpoint = coverage_id,
  version = "2.0.1",
  method = NULL,
  format = "image/tiff;application=geotiff",
  epsg = 3035,
  interpolation = NULL,
  ...
)

Arguments

coverage_id

Coverage ID. When in doubt, inspect the GetCapabilities of the service.

endpoint

Endpoint to interface. Note that wcs_ is appended and only the rest of the product name must be provided. For example, wcs_dgm200_inspire becomes dgm200_inspire. Defaults to the value of coverage_id.

version

Service version of the WCS. Defaults to 2.0.1.

method

HTTP method to use for the request. GET requests provide parameters using URL queries. Filters must be provided as CQL queries. While this is less error-prone, it allows a maximum number of only 2048 characters. Especially when providing more sophisticated spatial queries, GET queries are simply not accepted by the services. In these cases it makes sense to use POST requests instead.

If NULL, the method is inferred from the type of filter query provided to filter (either XML or CQL). If no filter is provided, the method is inferred from getOption("ffm_query_language").

format

Content type of the output. This value heavily depends the endpoint queried. Defaults to "image/tiff;application=geotiff".

epsg

Numeric value giving the EPSG identifier of the coordinate reference system (CRS). The EPSG code is automatically formatted in a OGC-compliant manner. Note that not all EPSG codes are supported. Inspect the GetCapabilities of the target service to find out which EPSG codes are available. Defaults to EPSG:3035.

interpolation

Method used to interpolate the coverage raster. Allowed methods depend on the capabilities of the WCS.

...

Further parameters passed to the WFS query. In case of POST requests, additional namespaces that may be necessary to query the WFS. Argument names are interpreted as the prefix (e.g. xmlns:wfs) and argument values as namespace links.

Value

A SpatRaster.

Examples


# Boundaries can be provided using two subset arguments
bkg_wcs(
  "dgm200_inspire__EL.GridCoverage",
  endpoint = "dgm200_inspire",
  subset = "E(548282,552280)",
  subset = "N(5800943,5804942)"
)

BKG WFS

Description

Low-level interface to BKG-style web feature services (WFS). This function is used in all high-level functions of ffm that depend on a WFS, e.g., bkg_admin.

bkg_feature_types lists all available feature types for a given endpoint.

Usage

bkg_wfs(
  type_name,
  endpoint = type_name,
  version = "2.0.0",
  method = NULL,
  format = "application/json",
  layer = NULL,
  epsg = 3035,
  properties = NULL,
  filter = NULL,
  server = sgx_base(),
  ...
)

bkg_feature_types(endpoint, server = sgx_base())

Arguments

type_name

Feature type of the WFS to retrieve. You can use bkg_feature_types to retrieve a list of feature type names for a given endpoint.

endpoint

Endpoint to interface. Note that wfs_ is appended and only the rest of the product name must be provided. For example, wfs_vg250 becomes vg250. Defaults to the value of type_name.

version

Service version of the WFS. Usually 2.0.0, but some services still use 1.0.0 or 1.1.0.

method

If NULL, the method is inferred from the type of filter query provided to filter (either XML or CQL). If no filter is provided, the method is inferred from getOption("ffm_query_language").

format

Content type of the output. This value heavily depends the endpoint queried. Most services allow application/json but some only support GML outputs. When in doubt, inspect the GetCapabilities of the target service. Defaults to "application/json".

layer

If format specifies a GML output, layer specifies which layer from the downloaded GML file to read. Only necessary if the GML file actually contains multiple layers. Defaults to NULL.

epsg

properties

Names of columns to include in the output. Defaults to NULL (all columns).

filter

A WFS filter query (CQL or XML) created by wfs_filter.

server

WFS server domain to use. Defaults to the SGX spatial data center of the BKG.

...

Value

An sf tibble

Examples


bkg_feature_types("vg5000_0101")

bkg_wfs(
  "vg5000_lan",
  endpoint = "vg5000_0101",
  count = 5,
  properties = "gen",
  epsg = 4326
)[-1]

# Filters are created using `wfs_filter()`
bkg_wfs(
  "vg5000_krs",
  endpoint = "vg5000_0101",
  properties = "gen",
  filter = wfs_filter(sn_l == 10)
)[-1]

German NUTS `MULTIPOLYGON`s

Description

Three sf dataframes containing all geometries of German NUTS1, NUTS2, and NUTS3 regions, respectively. The reference year is 2023.

These datasets can be very useful for quickly retrieving pre-loaded boundaries without download.

Usage

bkg_nuts1

bkg_nuts2

bkg_nuts3

Format

For the dataframe format, see bkg_nuts.

An object of class sf (inherits from tbl_df, tbl, data.frame) with 38 rows and 7 columns.

An object of class sf (inherits from tbl_df, tbl, data.frame) with 400 rows and 7 columns.

Source

Examples

bkg_nuts1

WFS filters

Description

Utility functions to construct XML or CQL queries. These functions are the backend of the filter argument in the filter capabilities of all ffm functions that interact with a WFS (e.g., bkg_admin, bkg_clc or bkb_geonames).

Usage

wfs_filter(
  ...,
  filter = NULL,
  bbox = NULL,
  poly = NULL,
  predicate = "intersects",
  geom_property = "geom",
  default_crs = 25832,
  lang = NULL
)

Arguments

...

R	CQL	XML
`==`	`=`	`PropertyIsEqualTo`
`!=`	`<>`	`PropertyIsNotEqualTo`
`<`	`<`	`PropertyIsLessThan`
`>`	`>`	`PropertyIsGreaterThan`
`>=`	`>=`	`PropertyIsGreaterThanOrEqualTo`
`<=`	`<=`	`PropertyIsLessThanOrEqualTo`
`%LIKE%`	`LIKE`	`PropertyIsLike`
`%ILIKE%`	`ILIKE`
`%in%`	`IN`	`PropertyIsEqualTo` and `Or`

filter

A character string containing a valid CQL or XML filter. This string is appended to the query constructed through .... Use this argument to construct more complex filters. Defaults to NULL.

bbox

poly

predicate

geom_property

Name of the geometry property included in the WFS. In most cases, this is "geom", but there are some exceptions.

default_crs

A WFS defines a default CRS in which coordinates for spatial filtering have to be provided. For BKG services, this is usually EPSG:25832. All sf objects provided through bbox or poly are first transformed to this CRS before creating the query.

lang

Query language to use for constructing the query. One of "cql" and "xml". By default, almost all ffm functions use CQL because it is simpler and less prone to errors. However, CQL is limited in terms of query size. Especially when providing a poly, URLs can become so long that the WFS server will decline them. XML can be a valid alternative to construct large queries. Additionally, some services like the one used by bkg_geonames only support XML. If NULL, defaults to getOption("ffm_query_language").

Value

A CQL query or an XML query depending on the lang argument.

Examples

# CQL and XML support mostly the same things
wfs_filter(ags %LIKE% "05%", lang = "cql")
wfs_filter(ags %LIKE% "05%", lang = "xml")

bbox <- c(xmin = 5, ymin = 50, xmax = 7, ymax = 52)
wfs_filter(bbox = bbox, lang = "cql")
wfs_filter(bbox = bbox, lang = "xml")

# Using `filter`, more complex queries can be built
wfs_filter(ars %LIKE% "%0", filter = "regierungs NOT IS NULL")

wfs_filter(
  filter = "<fes:Not>
    <fes:PropertyIsNull>
      <fes:ValueReference>aussprache</fes:ValueReference>
    </fes:PropertyIsNull>
  </fes:Not>",
  lang = "xml"
)

German administrative boundaries

Description

Usage

Format

Source

See Also

Examples

Administrative areas

Description

Usage

Arguments

Value

Query language

See Also

Examples

Administrative hierarchy

Description

Usage

Arguments

Value

Examples

Official keys

Description

Usage

Arguments

Value

Query language

Examples

Airports

Description

Usage

Arguments

Value

Query language

See Also

Examples

Area code regions

Description

Usage

Arguments

Value

Query language

Examples

Regions of authority

Description

Usage

Arguments

Value

Query language

See Also

Examples

Corine Land Cover

Description

Usage

Arguments

Value

Query language

See Also

Examples

Border crossings

Description

Usage

Arguments

Value

Query language

See Also

Examples

Digital elevation model

Description

Usage

Arguments

Value

Examples

Digital landscape model (DLM)

Description

Usage

Arguments

Value

Query language

See Also