shape rendering in nodejs with LearnBoost's node-canvas

Node.js server for composing map tiles using modestmaps.js

This example demonstrates a Node.js server that dynamically composes map tiles into a single static image. The HTTP endpoint `/map` accepts zoom, latitude, longitude, width, and height parameters, then uses the modestmaps.js library to calculate which tiles are needed, fetches them via the `get` library, and draws them onto a Canvas using the `canvas` package. The OpenStreetMap tile provider is referenced directly, and the final composite is returned as a PNG.

RRandomEtc

72% match

d3.geoPath + node-canvas

This example demonstrates how to render geographic data to a Canvas element using d3.geoPath with node-canvas, producing a stroked mesh of United States county boundaries. The rasterize script loads US Atlas TopoJSON data, converts it to GeoJSON with topojson-client, and passes it through d3.geoPath’s context method to draw paths into a 960×600 canvas. It then writes the resulting bitmap to a PNG file, showing server-side vector-to-raster conversion without a browser.

71% match

Leaflet.js × D3.js × geojson-vt.js - Redraw Canvas Tiles Map

This example shows a slippy map interface using Leaflet.js alongside D3.js to render geographic boundaries from a GeoJSON dataset. Canvas tiles are generated in the frontend, converting vector data into raster tiles on demand. The core function `addCanvasTile` leverages the `geojson-vt.js` `tileIndex.getTile` API to extract features for a given zoom level and coordinate. Drawing occurs directly on HTML5 canvas elements, and the code uses Canvas `getImageData` to enable click detection on rendered polygons, with D3 selection handling mouse events for property feature identification.

HHirosaji

70% match

Streaming Shapefile

This example streams a 12.9MB shapefile of US county boundaries directly from a remote URL, rendering each feature to a Canvas as it downloads. The map uses an Albers USA projection with a 0.5-pixel stroke, and parsing is handled incrementally by the shapefile library’s `open` and `read` promise chain. The `d3.geoPath` generator draws the geometry, and the browser’s streaming fetch support enables the full map to appear before the download completes.

68% match

Image Processing

This example demonstrates real-time image processing on map tiles using Polymaps and HTML5 Canvas. The map loads a static image from a URL and renders it through a custom canvas layer, where each tile’s pixel data is read with `getImageData` and halved in intensity before being written back via `putImageData`. The code uses `po.canvas()` to define the layer, `drawImage` to place the source, and `createImageData` to prepare the output. The result shows a visibly darkened version of the original image across the panning map.

d3.geoPath + Canvas

This example displays a map of the United States drawn entirely on a Canvas element. It shows how D3’s `d3.geoPath` can render geographic data into a native Canvas context rather than an SVG, with the map’s geometry provided by the `us-atlas` dataset. The code uses `d3.json` to load the TopoJSON file and `topojson.mesh` to convert it into renderable shapes. The resulting path is stroked onto the canvas via the `context` set on `d3.geoPath`, demonstrating a performant alternative to SVG for large spatial datasets.

A D3 Map, points plotted with canvas instead of SVG

This example shows a zoomable map of Manhattan with tree locations from a CSV file, plotted as red circles. It uses D3 v3 for map tile fetching and projection, while rendering the points onto a Canvas 2D context instead of SVG for performance. The code demonstrates a hybrid approach where D3's `d3.geo.tile` and `d3.geo.mercator` handle geographic transforms, and the canvas context draws arcs at projected coordinates. Zooming and panning trigger redraws, and the mouse position is displayed with latitude/longitude.

SShweta-tech

Dynamic tile masking and more

This example demonstrates interactive masking of OpenStreetMap tiles over a stamen.com toner base map, controlled by user-drawn polygons. Using Leaflet’s draw control, users create shapes that act as SVG masks, revealing or hiding the underlying OSM tile layer. The visualization also applies SVG filters, such as grayscale, hue rotation, and sepia, to the map tiles, and offers a selection of hatch patterns for the mask fills. The code integrates D3.js (v3) for projecting GeoJSON geometries into Leaflet’s coordinate system and manipulates the SVG `defs` and mask elements directly.

KKoGor