Geocoding example - uses PDOK LocationServer

100%

Geocoding example - uses PDOK LocationServer

✓ Published0🌍 Public

Last edited Dec 22, 2019

Created on Dec 22, 2019

This example demonstrates geocoding Dutch childcare locations by mapping street addresses to geographic coordinates. It shows the first 100 entries from a national childcare registry, displaying their matched BAG object IDs and centroid coordinates. The code uses the `httr` package to query the PDOK LocationServer API, while `dplyr` and `purrr` handle data manipulation and iterative geocoding. The input data is sourced from a CSV file provided by the Landelijk Register Kinderopvang. Each address is processed through the API’s free endpoint, returning the closest match’s details, which are then combined with the original dataset for display.

AI-generated description

Similar vizzes

Loading thumbnail…

Geocoding van adressen met LocatieServer en Power Query in Power BI

This example demonstrates geocoding of childcare facility addresses from a Dutch open dataset by enriching it with geographic coordinates and neighborhood codes. It shows how Power Query in Power BI transforms tabular address data into mapped points. The workflow uses the LocatieServer API (nationaalgeoregister.nl) to fetch JSON responses, extracting attributes like wijkcode, buurtcode, and centroid coordinates. It constructs URLs from combined address fields, parses the JSON documents with `Json.Document`, and splits the resulting `centroide_ll` coordinates into separate longitude and latitude columns using `Table.SplitColumn`. The final table removes helper columns, leaving ready-to-use spatial data for visualization.

FFrieseWoudloper

72% match

Loading thumbnail…

Gist ed318d44833c6e35336fbf5dff774017

This example visualizes Dutch neighborhood-level geographic data by combining CBS microsubsidy statistics with municipal boundary geometries. It first fetches neighborhood polygons from the national georegister WFS service, parsing the Well-Known Text geometry strings, and then joins these with the statistical dataset. The visualization maps the subsidy figures onto the neighborhood shapes, likely using a choropleth approach to show geographic distribution. The code relies on the `cbsodata` API for the statistical data and pandas for data manipulation, while the geometries are loaded directly from the WFS endpoint.

FFrieseWoudloper

62% match

Loading thumbnail…

R script om te demonstreren hoe je WFS paging kunt implementeren in R

This example shows how to retrieve all Dutch address objects (verblijfsobjecten) in the town of Zuidhorn from the BAG Web Feature Service (WFS) using paging to handle large result sets. The code first queries the server’s maximum page size via GetCapabilities, then counts matching features, and finally fetches them page by page using `startindex` while sorting by identifier. It uses the `httr`, `xml2`, and `sf` R packages to parse the WFS responses and convert the resulting GeoJSON into simple features, which are then mapped with the `tmap` package. The data source is the national georegister’s BAG WFS endpoint.

FFrieseWoudloper

60% match

Loading thumbnail…

Power BI query om onvolledige en foute adressen van provinciehuizen te verbeteren en verrijken met LocatieServer

This Power Query example cleans and enriches incomplete or incorrect addresses of provincial government buildings (provinciehuizen) by geocoding them through the LocatieServer API. It first transforms the input address list, then constructs a URL query for the Nationaal Georegister’s free geocoding endpoint, fetching JSON attributes like postcode, street name, and coordinates. Using Power Query’s table functions (`Table.AddColumn`, `Table.ReplaceValue`, `Table.SplitColumn`), it extracts longitude and latitude, then removes intermediate columns. The data source is a hardcoded gist list, and the output includes structured address components and map-ready coordinates.

FFrieseWoudloper

59% match

Loading thumbnail…

Plotting points test

This example visualizes parking lot data retrieved from the RDW Open Data API, plotting geographic points onto a map of Dutch municipalities. The map uses an SVG rendering with a Mercator projection, and the geographic boundaries are drawn from a TopoJSON file using `d3.geoPath`. The parking point coordinates are extracted from the API’s geometry text fields and displayed as circles on the map. The visualization incorporates `d3.zoom` for panning and zooming the view, allowing users to explore the spatial distribution of the plotted points.

GGijs Laarman

59% match

Loading thumbnail…

Plotting points test

This visualization plots geographic points from Dutch parking data onto a map of municipalities. The code uses d3.geoMercator projection and d3.geoPath to render the map from TopoJSON data, while fetching point coordinates from an RDW Open Data API. Circles are drawn in red for each location, using projection to convert longitude and latitude into SVG coordinates. The map inherits municipal boundaries from the cartomap.github.io TopoJSON source with hover fill transitions.

Mmbergevoet

59% match

Loading thumbnail…

Gist 5053ebcce793d11bc765

This example maps all Dutch municipalities in 2014, highlighting those with fewer than 20,000 residents in red on top of the full country outline. It uses the `rgdal` and `rgeos` libraries to read shapefile data from a ZIP downloaded from twiav.nl, then computes population density via `gArea()` and identifies the least dense municipality. The visualization shows a static choropleth-style base map with an overlaid selection, while also printing tabular summaries like counts per safety region and the names of the least dense area. It does not animate or use interactive frameworks, relying solely on base R plotting.

FFrieseWoudloper

58% match

Loading thumbnail…

Plotting points backup

This example displays parking location data as red dots on a map of Dutch municipalities, sourced from the RDW open data API. The map uses a Mercator projection with `d3.geoPath` to render the TopoJSON boundaries. Parking coordinates are extracted from the API’s geometry field, filtered, and plotted as small circles on the SVG. The visualization supports zooming via d3-zoom and includes interactive hover effects on the municipality paths.

Mmbergevoet

58% match