Gist c8b3e33ae90180e985646e1ef4876dfe

Gist f1a627d4af91444f3fcaea66c62c8319

A Leaflet map centered on France displays a circular buffer polygon around a point at coordinates (2.18, 46). The example uses proj4js and the reproject library to convert the point from WGS84 to EPSG:3857, then applies jsts.io.GeoJSONReader to read the geometry and create a 40,000-meter buffer via the jsts buffer method. After writing the buffered geometry back to GeoJSON, it reprojects to WGS84 and renders the result as a Leaflet GeoJSON layer on OpenStreetMap tiles, with a scale control and a marker at (0,0).

71% match

Gist 32329a8557135f11cb5656e3bfd4d35c

A WebGL map visualizes the locations of French tobacco shops, using points to show their distribution. The code geocodes addresses from an official customs dataset via the data.gouv.fr API, then processes the CSV with the `requests` library. It uses a Vue.js front-end to render the points in a 3D space, allowing users to explore the spatial patterns of the shops.

Gist b3d6991a9d7ab3de6f7f13e7ed38e097

This map shows the municipal arrondissements of Lyon and Marseille in France, with each district colored according to its population. The visualization loads GeoJSON data describing the polygon boundaries of each arrondissement and uses the ogr2ogr library to convert the shapefile data. The interactive display, viewed through GeoJSON.io, renders the geographic features using standard web mapping tools and displays the population values stored in each polygon's properties when the user clicks or hovers over a district.

Gist 96068363e74b4c1c148c55aad9ab0cf4

This example demonstrates client-side reprojection of GeoJSON geometries from a source CRS to WGS84 using the Proj4js library. It fetches a French “quartiers prioritaires” dataset encoded in EPSG:2154 and transforms its Point, LineString, Polygon, and Multi* geometries via custom functions that recursively map coordinates through a proj4 transformer. It also tests a second transformation from EPSG:4326 to EPSG:3857 on sample geometries, logging converted coordinates to the console. The code relies on proj4.defs, proj4(...).forward, and the fetch API.

Gist e6f4c2723682e0180ff0bbf59f417beb

This interactive map of French dams displays their locations as points across the country, with each point linking to a detailed information page. The visualization is built from a GeoJSON FeatureCollection of dam properties, including height, reservoir volume, river, and owner. The data was cleaned and enriched using shell scripting and the `jq` command-line tool, with the final map likely rendered using a library such as Leaflet or Mapbox. The code shows the use of `ogrinfo` and `ogr2ogr` for geospatial data processing and SQL queries to transform the attributes.

Gist 4ab7840c00aa352f278636ea3f3f0d3e

This example demonstrates streaming merge of two French cadastral parcel GeoJSON files into a single unified feature collection, output as a continuous JSON stream to standard output. It shows how to combine multiple geospatial datasets without loading them entirely into memory. The code uses the `geojson-stream` library for parsing and stringifying GeoJSON features, Node.js `fs.createReadStream` for file input, and the `zlib` module to decompress gzipped source files. Data originates from the Etalab cadastre dataset, with separate scripts handling zipped and unzipped input files.

Extrait datatourisme bibliothèques Nouvelle Aquitaine

This map visualization displays the locations of libraries across Nouvelle-Aquitaine, France, sourced from the DATAtourisme dataset via data.gouv.fr. It shows each library as a point on a geographic map, highlighting their distribution throughout the region. The code downloads the dataset, filters entries using `xsv search` for the Library category, and converts CSV records to GeoJSON features with latitude and longitude coordinates. The resulting GeoJSON file is suitable for rendering with a Vue.js framework, likely using a mapping library to display the geographic points.

69% match

Récupération geolocalisation EHPAD 57

This example visualizes the geographic distribution of EHPAD (nursing homes) in the Moselle department (57) of France, displaying each facility as a point on a map. The data is retrieved from a public government API and converted to GeoJSON format using `jq` command-line tools for filtering and restructuring. The visualization is built with the Vue framework, rendering the geographic points to show facility locations, with additional property information such as name, city, and legal status included for reference. The map uses standard GeoJSON `Point` features to represent each facility's coordinates.