Gist 8393727

Gist 10676346

This map displays labeled points from a GeoJSON file, plotting locations like "Internet Archive," "China," and "New York" at their geographic coordinates. The visualization likely renders a large-scale point cloud, with overlapping labels suggesting a messy or aggregated dataset. Using a mapping library, likely D3.js with `d3.geoPath` for drawing map features and standard SVG or Canvas techniques for placing text labels, the code creates a simple geographical scatter plot. The rendering emphasizes the spatial distribution of these named places across the globe.

CCliffordAnderson

76% match

Gist 8393725

The visualization displays a GeoJSON point dataset of named locations—such as Traino, Cascata, and Neviera—near a specific area in Italy, each with a YouTube link. It uses D3.js with a force-directed simulation (`d3.forceSimulation`) to position the points on a map, while `d3.geoPath` renders the geographic features. The points are colored and labeled, and hovering or clicking likely reveals the associated video link. The code relies on the GeoJSON structure for both location data and map boundaries.

75% match

Gist 8392781

This visualization maps lake locations across the Adirondack region using a GeoJSON FeatureCollection, plotting each named water body as a point based on its coordinates. The code uses D3.js to render the geographic data, likely with `d3.geoPath` to draw the map context and `d3.forceSimulation` to position or adjust the points. The map shows the spatial distribution of ponds and lakes, with labels revealing their names and the year 2002 as the dataset’s reference. The rendering relies on SVG paths and projected coordinates to display the terrain.

75% match

Gist 8393709

This visualization displays a world map rendered from GeoJSON data using D3.js, with country polygons colored according to a categorical scale. The map focuses on named regions and includes a legend and hover interactions, allowing viewers to explore geographic boundaries and associated metadata such as country names and people listed in the properties.

74% match

Gist 8393657

This example maps two geographic points from a GeoJSON FeatureCollection onto a world map using D3’s `d3.geoPath` and a geographic projection. It then runs a force-directed simulation with `d3.forceSimulation`, treating the points as nodes that repel each other while being constrained by the map’s bounds. The visualization shows how the points drift and settle under the force layout, with their positions updated via D3’s data join. The code relies on the `Octomonster.geojson` file for the initial coordinates and uses Canvas rendering for the map and points.

Gist 8393692

This example displays two geolocated markers on a map, each with a title and description of a building. It uses a `map.geojson` file as the data source, containing point features with custom properties for labels and colors. The visualization renders the map using D3’s `d3.geoPath` to draw the geographic features, while the markers are positioned based on their coordinates. The code relies on D3’s force simulation (`d3.forceSimulation`) to potentially handle marker placement or interaction, though the static view shows the two points plotted directly.

Gist 6245338

This visualization maps three Spanish cities as individual points on a geographic projection, with each point represented by a small dot. It uses a custom map projection and renders the GeoJSON features as a filled landmass, while the city markers are drawn as circles. The code relies on `d3.geoPath` to project and draw the map geometry, and `d3.forceSimulation` is not used here; instead, the points are placed directly at their projected coordinates. The canvas API (`getContext('2d')`) handles all rendering, and the map’s geographic boundaries come from the embedded `map.geojson` FeatureCollection.

PPhilippe Rivière

Gist 8393715

This example visualizes a set of geolocated points in the Matera, Italy area as a static scatterplot. The code loads a GeoJSON GeometryCollection of point coordinates and plots them using D3’s geographic projection, with `d3.geoPath` to render the geometry. The points represent recorded signals or reports, and their spatial distribution reveals clusters around certain urban zones. The visualization uses D3’s data-binding to draw circles for each coordinate, with no interactive or animated behavior, relying solely on the projection and canvas rendering to communicate the location pattern.