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Read a PDOK layer as an sf object

Source: R/pdok_read.R
pdok_read.Rd

Loads a layer from PDOK as a simple feature collection over the OGC API Features service, handling pagination automatically.

Usage

pdok_read(
  dataset,
  layer,
  bbox = NULL,
  filter_by = NULL,
  predicate = "intersects",
  datetime = NULL,
  crs = NULL,
  max_features = NULL
)

Arguments

dataset

A dataset id from pdok_list_datasets() (e.g. "cbs/gebiedsindelingen"), or a raw OGC API base URL.

layer

A layer id from pdok_list_layers().

bbox

Optional server-side bounding-box pre-filter: a numeric vector c(xmin, ymin, xmax, ymax) (assumed CRS84) or an sf/sfc/bbox object whose extent is used.

filter_by

Optional sf/sfc geometry to filter the result by. Its bounding box is used as a cheap server-side pre-filter, and the result is then filtered exactly with pdok_filter_by(). This is the one-call form of the load-then-filter workflow. It is usually a polygon (e.g. a municipality), but a point works too: filtering an area layer by a point returns the feature that contains it (for example the municipality an address falls in).

predicate

Spatial predicate for filter_by, passed to pdok_filter_by() (default "intersects"). See its Spatial predicates section for the available options, and sf::geos_binary_pred for their definitions.

datetime

Optional temporal filter: a single year (e.g. 2026, mapped to a mid-year instant), an OGC datetime string, or an interval such as "2020-01-01/2025-12-31".

crs

Optional output CRS as an EPSG code (e.g. 28992 for RD New). NULL keeps the source CRS.

max_features

Optional cap on the number of features returned.

Value

An sf object with one row per feature, the layer's attribute columns, and a geometry column. A zero-row sf is returned (with a warning) when nothing matches.

Details

By default the data is returned in the coordinate reference system the service provides (lon/lat, CRS84, for the OGC path). Set crs to receive the data in another CRS; the transformation is done client-side with sf::st_transform().

See also

pdok_list_layers() to find layer ids.

Examples

# \donttest{
# A whole layer: the Dutch national parks
parks <- pdok_read("rvo/nationale-parken-geharmoniseerd", "protectedsite")
#> ⠙ Downloading PDOK features: 22 fetched

# Municipalities for 2024, in RD New (EPSG:28992)
pdok_read(
  "cbs/gebiedsindelingen", "gemeente_gegeneraliseerd",
  datetime = 2024, crs = 28992, max_features = 5
)
#> Simple feature collection with 5 features and 8 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 136985.7 ymin: 473841.6 xmax: 269937.9 ymax: 592658.9
#> Projected CRS: Amersfoort / RD New
#> # A tibble: 5 × 9
#>   einddatum              id jaarcode jrstatcode rubriek  startdatum         
#> * <dttm>              <int>    <int> <chr>      <chr>    <dttm>             
#> 1 2024-12-31 23:59:59     1     2024 2024GM0014 gemeente 2024-01-01 00:00:00
#> 2 2024-12-31 23:59:59     2     2024 2024GM0034 gemeente 2024-01-01 00:00:00
#> 3 2024-12-31 23:59:59     3     2024 2024GM0037 gemeente 2024-01-01 00:00:00
#> 4 2024-12-31 23:59:59     4     2024 2024GM0047 gemeente 2024-01-01 00:00:00
#> 5 2024-12-31 23:59:59     5     2024 2024GM0050 gemeente 2024-01-01 00:00:00
#> # ℹ 3 more variables: statcode <chr>, statnaam <chr>,
#> #   geometry <MULTIPOLYGON [m]>

# One-call area filter: national parks within the province of Utrecht
provinces <- pdok_read(
  "cbs/gebiedsindelingen", "provincie_gegeneraliseerd", datetime = 2024
)
utrecht <- provinces[provinces$statnaam == "Utrecht", ]
parks_utrecht <- pdok_read(
  "rvo/nationale-parken-geharmoniseerd", "protectedsite",
  filter_by = utrecht
)
# }