R-script voor het downloaden en converteren van een JSON-bestand met locaties van jachthavens converteren naar shape-bestand

100%

R-script voor het downloaden en converteren van een JSON-bestand met locaties van jachthavens converteren naar shape-bestand

✓ Published0🌍 Public

Last edited Feb 9, 2016

Created on Oct 17, 2015

This example demonstrates how to download JSON data containing marina locations from a Dutch tourism website and convert it into a shapefile. The script shows the process of fetching data via an HTTP POST request with a custom header, parsing the JSON response, extracting attributes like address and contact details from nested HTML, and then transforming geographic coordinates from WGS84 to the Dutch RD coordinate system using the `sp` and `rgdal` packages. It uses `httr` for the API request, `jsonlite` for JSON parsing, and `XML` for handling HTML content within the JSON. The final shapefile is written with `writeOGR`.

AI-generated description

Similar vizzes

Loading thumbnail…

R-script voor het downloaden en georefereren van een OpenStreetMap tile

This R script downloads a single OpenStreetMap tile centered on the Martinitoren in Groningen and georeferences it by generating a World file. It first converts latitude and longitude coordinates to tile coordinates using the slippy map tilenames algorithm, then fetches the PNG from the `tile.openstreetmap.org` server. The script calculates the tile’s bounding box from the zoom level and writes a six-line `.pgw` file with pixel-to-world transformation parameters, enabling the image to be overlaid with geographic data in GIS software. The code uses base R functions like `download.file`, `paste0`, and `writeLines` without external libraries.

FFrieseWoudloper

68% 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

65% match

Loading thumbnail…

R-script dat aan de hand van de gegevens uit het objectenportaal van de provincie Groningen, de BAG en de Zonneatlas bepaald welke panden van de provincie Groningen wel/niet geschikt zijn voor het opwekken van zonne-energie

This R Markdown analysis determines which buildings in the province of Groningen are suitable for solar energy generation, based on open data from the provincial object portal, the BAG (Basisregistratie Adressen en Gebouwen), and the Zonatlas. It shows the workflow from downloading building and address data via WFS APIs to converting address objects into building polygons using the `httr`, `sp`, and `rgdal` packages. The script also integrates municipal boundaries to apply the correct Zonatlas layer, producing a reproducible geospatial assessment.

FFrieseWoudloper

62% match

Loading thumbnail…

ArcGIS Online hosted feature service in lezen in R

This example demonstrates how to read and visualize the Dutch national heritage register (Rijksmonumenten) from an ArcGIS Online hosted feature service. It shows the full workflow of querying the service's metadata, counting features, and paginating through all 64,020 records, then maps them with `tmap` and `sf`. The code uses the `httr` and `jsonlite` packages to construct URL requests and parse JSON, while `sf::st_read()` reads the GeoJSON response. It explicitly checks pagination support via the service’s `advancedQueryCapabilities` and explains an anomaly where the initial page returns more records than `maxRecordCount` suggests. The final map is rendered with `qtm()`, and summary statistics (min/max OBJECTID) are computed via the service’s `outStatistics` parameter.

FFrieseWoudloper

62% match

Loading thumbnail…

Oefenen met scale

This example demonstrates how to load and display geographic boundary data from a Web Feature Service (WFS) endpoint using D3.js. It shows a map of Dutch arrondissementsgebieden (judicial districts) for 2019, projected with a Mercator projection. The code uses `d3.json` to fetch GeoJSON from the national georegister WFS, then renders it as SVG paths via `d3.geo.path` with a `d3.geo.mercator` projection. A simple alert greets viewers before the visualization loads, and the SVG canvas is sized to 960 by 500 pixels.

FFrieseWoudloper

62% match

Loading thumbnail…

met wfs en geojson als output formaat

This example shows how to load and display GeoJSON data that has been retrieved from a WFS (Web Feature Service) and converted to TopoJSON format. The map renders the Dutch municipal boundaries as SVG paths using D3 v4. The data pipeline is notable: GeoJSON in EPSG:4326 is fetched from a WFS, the winding order of the polygons is reversed in FME, and the result is written to TopoJSON. The visualization displays the topology-encoded arcs, demonstrating the boundary polygons of Dutch municipalities with a minimal, functional style typical of D3 examples.

FFrieseWoudloper

61% match

Loading thumbnail…

Gist d214dcd214bbefa0eeb55b6f7d209c33

This visualization shows a TopoJSON map of Dutch administrative regions, rendered as vector shapes defined by coordinate arcs. The data file, named "arrondissementsgebieden.json" (Dutch for "districts areas"), contains geospatial boundary data that is displayed as a static map. The arcs encode the outlines of the regions, and the visualization likely uses D3.js or similar to project and render these coordinates as an interactive or static choropleth-style map, though no styling or color encoding is present in the raw data. The example demonstrates how raw topological data can be parsed and displayed as a map of regional boundaries.

FFrieseWoudloper

61% match

Loading thumbnail…

Gist 7a936b232f3444758c3bfc5775324231

This example shows a static map of Dutch arrondissements (districts) for 2019, rendered as a single SVG path using a Mercator projection. The code loads GeoJSON data from a national georegister Web Feature Service (WFS) endpoint via `d3.json`. It uses `d3.geo.mercator` and `d3.geo.path` to project and draw the geographic features. The visualization is minimal, displaying only the district boundaries without additional styling or interactivity.

FFrieseWoudloper

60% match