⚡ GMapsBook.com is crafted by Jozef Sorocin (🟢 Book a consulting hour) and powered by:

g-Xperts (Google Cloud & Business Profile Partner)
Spatialized.io (Elasticsearch & Google Maps consulting).
and Garages-Near-Me.com (Effortless parking across Germany)

In the parent chapter we briefly explored Google Maps’ native transit layer.

In this chapter, we’ll attempt to replicate this layer using publicly available GeoJSON data and learn a thing or two about Google Maps’ interactive data layers.

Scenario

I’m a city planner analyzing the proximity of New York City subway lines to new developments.

To start off, I’d like to view and highlight the metro lines:

https://storage.googleapis.com/gmaps-handbook/public/common/5/5.1/highlighting-nyc-subway-lines.mp4

Approach

As you saw in the chapter on Turf.js & Exporting to GeoJSON, the GeoJSON format is a popular mechanism to encode and share geospatial data.

Finding the right data

Many cities, agencies, and non-profits publish valuable GeoJSON data online. In your case, the city agency of choice would be NYC Open Data. Searching for “subway lines” leads to a promising dataset. From there, under “Export”, you’ll need to copy the GeoJSON URL:

To quickly inspect the geometries and properties of this small dataset, you can use geojson.io.

Indeed, you’re dealing with a FeatureCollection containing features of the form:

{
  "type": "Feature",
  "properties": {
    "name": "A-C",
    "url": "<http://web.mta.info/nyct/service/>",
    "rt_symbol": "A",
    "objectid": "800",
    "id": "2000251",
    "shape_len": "2714.92372395"
  },
  "geometry": {
    "type": "LineString",
    "coordinates": [
      [-73.88075000161994, 40.674129666468296],
      [-73.89035800079188, 40.67270966767174]
    ]
  }
}