TagOverpass Turbo

How to extract highways and subway lines from OpenStreetMap as a shapefile

It’s possible to use Overpass Turbo to extract any object from the OpenStreetMap “planet” and convert it from a GeoJSON or KML file to a shapefile for manipulation and analysis in GIS.

Say you want the subway lines for Mexico City, and you can’t find a GTFS file that you could convert to shapefile, and you can’t find the right files on Sistema de Transporte Colectivo’s website (I didn’t look for it).

Here’s how to extract the subway lines that are shown in OpenStreetMap and save them as a GIS shapefile.

This is my second tutorial to describe using Overpass Turbo. The first extracted places of worship in Cook County. I’ve also used Overpass Turbo to extract a map of campgrounds

Extract free and open source data from OpenStreetMap

  1. Open the Overpass Turbo website and, on the map, search for the city from which you want to extract data. (The Overpass query will be generated in such a way that it’ll only search for data in the current map view.)
  2. Click the “Wizard” button in the top toolbar. (Alternatively you can copy the code below and paste it into the text area on the website and click the “Run” button.)
  3. In the Wizard dialog box, type in “railway=subway” in order to find metro, subway, or rapid transit lines. (If you want to download interstate highways, or what they call motorways in the UK, use “highway=motorway“.) Then click the “build and run query” button.
  4. In a few seconds you’ll see lines and dots (representing the metro or subway stations) on the map, and a new query in the text area. Notice that the query has looked for three kinds of objects: node (points/stations), way (the subway tracks), relation (the subway routes).
  5. If you don’t want a particular kind of object, then delete its line from the query and click the “Run” button. (You probably don’t want relation if you’re just needing GIS data for mapping purposes, and because routes are not always well-defined by OpenStreetMap contributors.)
  6. Download the data by clicking the “Export” button. Choose from one of the first three options (GeoJSON, GPX, KML). If you’re going to use a desktop GIS software, or place this data in a web map (like Leaflet), then choose GeoJSON. Now, depending on what browser you’re using, a couple things could happen after you click on GeoJSON. If you’re using Chrome then clicking it will download a file. If you’re using Safari then clicking it will open a new tab and put the GeoJSON text in there. Copy and paste this text into TextEdit and save the file as “mexico_city_subway.geojson”.
Overpass Turbo screenshot 1 of 2

Screenshot 1: After searching for the city for which you want to extract data (Mexico City in this case), click the “Wizard” button and type “railway=subway” and click run.

Overpass Turbo screenshot 2

Screenshot 2: After building and running the query from the Wizard you’ll see subway lines and stations.

Overpass Turbo screenshot 3

Screenshot 3: Click the Export button and click GeoJSON. In Chrome, a file will download. In Safari, a new tab with the GeoJSON text will open (copy and paste this into TextEdit and save it as “mexico_city_subway.geojson”).

Convert the free and open source data into a shapefile

  1. After you’ve downloaded (via Chrome) or re-saved (Safari) a GeoJSON file of subway data from OpenStreetMap, open QGIS, the free and open source GIS desktop application for Linux, Windows, and Mac.
  2. In QGIS, add the GeoJSON file to the table of contents by either dragging the file in from the Finder (Mac) or Explorer (Windows), or by clicking File>Open and browsing and selecting the file.
  3. Convert it to GeoJSON by right-clicking on the layer in the table of contents and clicking “Save As…”
  4. In the “Save As…” dialog box choose “ESRI Shapefile” from the dropdown menu. Then click “Browse” to find a place to save this file, check “Add saved file to map”, and click the “OK” button.
  5. A new layer will appear in your table of contents. In the map this new layer will be layered directly above your GeoJSON data.
Overpass Turbo screenshot 4

Screenshot 4: The GeoJSON file exported from Overpass Turbo has now been loaded into the QGIS table of contents.

Overpass Turbo screenshot 5

Screenshot 5: In QGIS, right-click the layer, select “Save As…” and set the dialog box to have these settings before clicking OK.

Query for finding subways in your current Overpass Turbo map view

/*
This has been generated by the overpass-turbo wizard.
The original search was:
“railway=subway”
*/
[out:json][timeout:25];
// gather results
(
// query part for: “railway=subway”
node["railway"="subway"]({{bbox}});
way["railway"="subway"]({{bbox}});
relation["railway"="subway"]({{bbox}});
/*relation is for "routes", which are not always
well-defined, so I would ignore it*/
);
// print results
out body;
>;
out skel qt;

How to make a map of places of worship in Cook County using OpenStreetMap data

The screenshot shows the configuration you need to find and download places of worship in Cook County, Illinois, using the Overpass Turbo website.

If you’re looking to make a map of churches, mosques, synagogues and other places of worship, you’ll need data. The Yellow Pages won’t help because you can’t download that. And Google Maps doesn’t let you have a slice of their database, either. That’s where OpenStreetMap comes in. It’s a virtual planet that anyone can edit and anyone can have for free.

First we need to figure out what tag people use to identify these places. Sometimes on OSM there are multiple tags that identify the same kind of place. You should prefer the one that’s either more accurate (and mentioned as such in the wiki) or widespread.

The OSM tag info website says that editors have added over 1.2 million places of worship to the planet using “amenity=place_of_worship”.

Now that we know which tag to look for, we need an app that will help us get those places, but only within our desired boundary. Open up Overpass Turbo, which is a website that helps construct calls to the Overpass API, which is one way to find and download data from OSM.

In the default Overpass Turbo query, there’s probably a tag in brackets that says “[amenity=drinking_fountain]”. Change that to say “[amenity=place_of_worship]” (without the quotes). Now change the viewport of the map to show only the area in which you want Overpass Turbo to look for these places of worship. In the query this argument is listed as “({{bbox}})”.

The map has a search bar to find boundaries (cities, counties, principalities, neighborhoods, etc.) so type in “Cook County” and press Enter. The Cook County in Illinois, United States of America, will probably appear first. Select that one and the map will zoom to show the whole county in the viewport.

Now that we’ve set the tag to [amenity=place_of_worship] and moved the map to show Cook County we can click “Run”. In a few seconds you’ll see a circle over each place of worship.

It’s now simple to download: Click on the “Export” button and click “KML” to be able to load the data into Google Earth, “GeoJSON” to load it into a GIS app like QGIS, or “save GeoJSON to gist” to create an instant map within GitHub.

Compiling and mapping Chicago-area campgrounds

I’m adding Chicago-area campgrounds to the Chicago Bike Guide to entice new users and to espouse the enjoyment of medium-distance bike camping (which I’ve now done officially once, earlier this year).

<The Chicago Bike Guide is available for Android and iOS.>

I’m taking a systematic approach to finding all the publicly-owned campgrounds in the area by looking at primary sources.

First, though, I’ve used Overpass Turbo to create a list of all existing campgrounds in OpenStreetMap. You can see a gist of these places.

Camp sites at Greene Valley forest preserve I mapped.

Camp sites at Greene Valley forest preserve I mapped.

The next method is to find out which campgrounds are operated by the county forest preserves, which are usually well-documented on their respective websites. Then I will look at state parks in Illinois, Indiana, and Wisconsin, operated by states’ respective Departments of Natural Resources (DNR). Next I will look at national parks and finally commercial campgrounds.

The app will display campground information such as alcohol rules, if cabins or lodging is available, and how you can get there (which trails or train lines).

I’ve so far mapped the campgrounds in two ways, as nodes and as areas. At the Greene Valley forest preserve in DuPage County, for example, I’ve mapped the 11 individual camp sites (see map), but at Blackwell forest preserve in the same county, I’ve mapped the area as the camp site (see map).

Blackwell has over 50 sites in a discrete area and it’s more efficient to map them as a single node, while Greene Valley had far fewer sites but scattered over a couple areas.

Cross-posted to Web Map Academy.

© 2017 Steven Can Plan

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