I grabbed all the parking lots from OpenStreetMap via Metro Extracts, which is going to be the most complete map of parking lots and garages.
Volunteer mappers, including me, drew these by tracing satellite imagery.
With the parking lots data in GIS, I can count their area in square feet, which comes out to 160,075,942.42. Convert that to square miles and you get 5.74.
5.74/227.3*100 = 2.5 percent
The last snapshot of parking lot data I have is from February 2016, when only 3.39 square miles of parking lots have been drawn.
There are still many more parking lots to be drawn!
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.
Extract free and open source data from OpenStreetMap
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.)
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.)
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.
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).
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.)
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”.
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.
Screenshot 2: After building and running the query from the Wizard you’ll see subway lines and stations.
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
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.
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.
Convert it to GeoJSON by right-clicking on the layer in the table of contents and clicking “Save As…”
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.
A new layer will appear in your table of contents. In the map this new layer will be layered directly above your GeoJSON data.
Screenshot 4: The GeoJSON file exported from Overpass Turbo has now been loaded into the QGIS table of contents.
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;
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.
There’s no open data* for this because churches don’t pay taxes, don’t have business licenses, and aren’t required to register in any way
This where OpenStreetMap (OSM) 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.
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.
Tutorial
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.
*You could probably get creative and ask a municipality for a list of certificates of occupancy or building permits that had marked “religious assembly” as the zoning use for the property.
OsmAnd has great offline mapping features but it was tedious to ensure I had all of the maps at the desired zoom levels for the three-city bike ride in southern Illinois (pictured).
My friend is going to pick up a unique bicycle in Ohio and ride it back to Chicago. He designed a good route on Google Maps but now he needs to save it to his smartphone so he doesn’t have to constantly load directions and use data and waste battery life.
I gave him these instructions:
The best way to get a mobile view of the route is to use the Google Maps print feature and save it as a PDF. Then transfer that PDF to your phone through the Dropbox app. Then, in the Dropbox app, mark the PDF file as a favorite so that it’s stored offline, onto the phone.
There’s probably an app that can do what he wants, but I don’t know about it. There are hundreds of “maps” apps to sort through in each the App Store for iOS and the Play Store for Android.
In fact, I’ve downloaded OsmAnd, an offline maps app, for my Android tablet. I installed it and tried to learn how to use it in order to follow a downstate, intercity bike camping route. The app, though, required that you zoom in to each part of the map you wanted to store and then press “download”.
I spent 30 minutes downloading parts of the map, manually panning to the next section, before I decided to instead obtain one of the Illinois Department of Transportation’s regional bike maps and just draw it on there and write out a “cue sheet” (turn by turn directions).
This position gives the smartphone an unimpeded view of the street but prevents the user from manipulating it.
I first used the Mapillary app on iPhone last fall, in August, and I uploaded one photo, of my arm, which I can’t delete from the website. I uploaded a couple more photos from a street in Roscoe Village in November.
This week, though, I uploaded 500 photos from a three mile journey on California and Milwaukee Avenues in Chicago – streets that no one else had photographed for the Mapillary street view service.
Mapillary is an open source (sort of) street view service, originally developed in Sweden, which allows the public to contribute photos taken with their smartphone app.
What’s “sort of” about Mapillary being open source is that it appears that the company owns the photos once you upload them. People are free to use the photos to edit OpenStreetMap, or publish elsewhere – for personal use only – with attribution that adheres to Creative Commons 4.0. People who want to use the photos in a commercial application must subscribe to a pay service.
Mounting an iPhone to a bicycle
I took the jump from contributing nothing to uploading a whole lot because I bought an iPhone mount for my bicycle. After months of research – okay, chalk it up to my being lazy and it being really cold outside – I settled on the DgRock Universal Bicycle Mount from Amazon for $9. I was perplexed that there was a gap in choices between this decent $9 product and the next group, hovering around $30-40.
After three days of use, I’m satisfied, despite limitations that are present in all mounts I surveyed. The DgRock mount is solid, barely moves even as the bike bounces along Chicago’s pothole-ridden streets, and securely holds the iPhone with a strong, spring-loaded grip. It’s universal in two ways: it holds nearly any smartphone (it probably can’t hold one with a screen 5″ or larger) and it attaches to most bicycle handlebars.
The first day I used the DgRock mount Mapillary complained with a red icon that it couldn’t get a proper fix on its location and therefore it wouldn’t start photographing. Fine, I was in downtown Chicago where connecting to GPS satellites can be hard. I figured the wifi positioning system that all smartphones and tablets use would suffice.
There are problems with the mount, but I think these apply to all bicycle smartphone mounts: When the phone is in position to take photos, meaning its horizontal and level to the ground, you can’t see the screen. That’s because the screen, mounted on the handlebars, is much lower than your eyes and faces vertically, instead of angled towards your face. The only way around this, I believe, is to either get an upright bicycle (like my WorkCycles Fr8) or an adjustable lens (I can’t find any).
This position allows the user to manipulate the smartphone but you cannot take street view-style images.
The possible position angles of the smartphone when held by the mount was my main concern as I was shopping on Amazon: The mount need to have the flexibility to position the smartphone so its rear camera could be level with the ground. Smartphone mounts, though, are made to put the device in a position to be used and viewed frequently by the bicycle rider – it was unclear if many of the other smartphone mounts could accommodate the street view angles requirement.
The DgRock has no issue moving the iPhone into the right position, as you can see in the photos from my journey (or scroll to the end). Its issue, though, is that you have to put the smartphone in “backwards” so that the claw covers up part of the screen. I call it an issue but it doesn’t disturb the mount’s primary purpose when using Mapillary – the phone still has a clear view of the street.
Even with an upright bike like mine, though, it’s difficult to see the screen. I believe that Mapillary can actually design its app to help overcome this physical limitation.
Using Mapillary
The Mapillary app has improved greatly since the first version. It allows you to delete bad or undesired photos before uploading, and it has a simpler interface to go from opening the app to making your own street view. There are a couple changes I think would improve the user experience and lead to more contributions.
I would like to be able to turn off the screen while using Mapillary to save battery life. I think that the screen could fade to black and a small white dot or halo appears frequently to remind you that it’s working. I’d also like it to chime when iOS throws the “low storage” warning. Otherwise I may be riding along, thinking Mapillary is capturing the street, when iOS had actually run out of storage 10 minutes ago.
