Suivi avancement LIDAR copie de https://macarte.ign.fr/carte/322ea69dab4c7e5afabc6ec7043b5994/acquisitionslidarhd

Visualiser des données avec D3

This example displays a choropleth map of French administrative departments, coloring each region according to its population size using a sequential red color scale ranging from light to dark hues. The visualization renders the geographic boundaries as SVG paths via D3.js, employing the `d3.geo.path()` and `d3.geo.conicConformal()` projection APIs to transform the GeoJSON data, while population values from a CSV file are mapped to color classes using `d3.scale.quantile()`.

Ccedriccaijo

70% match

Display cadastre on Maplibre

This interactive map displays the French land registry, or cadastre, within the Maplibre GL rendering engine. It shows administrative boundaries—from regions down to individual communes—along with detailed cadastral sections, parcels, and buildings. Using the WebGL-driven Maplibre GL API, it loads vector tile sources from `openmaptiles.geo.data.gouv.fr`, with parcel lines appearing at zoom level 16 and property numbers labeled for identification. The styling, defined in a JSON style sheet, uses fill and line layers with conditional opacity to highlight parcels.

69% match

Gist 516c27edc013850e5fa703af9f9c0f03

This interactive visualization maps French EPCI administrative units using a force-directed layout, showing clusters of communes grouped by their intercommunality category. It uses d3.forceSimulation to position nodes representing each EPCI, with the underlying geoJSON data from the epci2020 file providing the administrative codes and names. The rendering translates the simulated node positions into geographic coordinates, allowing users to see the spatial distribution of these administrative groupings across France.

Depuis https://archeologie.culture.gouv.fr/fr

This visualization maps archaeological sites from the French Ministry of Culture's portal, presenting them as geographic points. The map is built with Vue, using GeoJSON data for site locations. Each data point is a clickable feature, with properties like title and description stored in the GeoJSON, and rendered using a mapping library that handles the geographic coordinates. The visualization shows the geographical distribution of French archaeological missions across the world, from the Île de Saï in Sudan to archaeological sites in Afghanistan.

France Map

A choropleth-style map of France displays each department as a white polygon with black outlines, based on GeoJSON data from a gist. The visualization uses D3 v3’s `d3.geo.path()` with a `d3.geo.conicConformal` projection, centered on the country and scaled to fit a 600×600 SVG canvas. Departments are loaded from `departments.json` and rendered as SVG `<path>` elements, with no data encoding beyond the geographical boundaries.

EElisaDnr

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.

TP3 DataViz 2024

A choropleth map displays waste tonnage (DEEE) across French departments for each year selected via a slider, with color intensity encoded by d3.scaleQuantize and hover tooltips. The visualization updates GeoJSON feature values per year and renders them using d3.geoConicConformal, d3.geoPath, and SVG. Data comes from a CSV on data.gouv.fr, filtered by waste type, while department boundaries use a simplified France GeoJSON from GitHub.

IInès Liroulet

Gist c8b3e33ae90180e985646e1ef4876dfe

This example demonstrates how to convert tabular JSON data containing longitude and latitude fields into a GeoJSON FeatureCollection using the command-line tool jq, making it ready for map-based visualization. The dataset covers digital mediation locations in the Auvergne-Rhône-Alpes region of France, sourced from data.gouv.fr. The transformation maps each original record into a GeoJSON Feature, preserving properties like name, address, services, and accessibility conditions, while constructing Point geometry from the coordinate pair. The code includes a preview image showing the resulting spatial distribution of these locations, though the visualization itself uses no specific JavaScript mapping library or framework beyond the jq conversion process.