Geographical objects and endonyms — bkg

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

...

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.

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

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.

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.

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.

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()