Converting Google My Maps to KML and GPX

Convert your routes that you made in Google My Maps to GPX so that you can view them on Garmin GPS devices, or upload them to MapMyRide.

  1. Access your My Map. Your My Map must have lines or routes in it. It appears that a My Map with only points doesn’t convert correctly.
  2. Click on View in Google Earth. Your web browser will download a KML file. It may automatically open in Google Earth, but this is not necessary.
  3. Visit GPS Visualizer to convert your KML file to GPX
  4. Select GPX as your output.
  5. For the input, choose the KML file you just downloaded from Google My Maps.
  6. Click Convert. Your file will be uploaded and your GPX file will be presented for download on the next page.
  7. Download your GPX file from the link on the page.

You can now transfer the GPX file to your GPS device, or upload it to MapMyRide. I confirmed that MapMyRide successfully imports the Google My Map I converted following these instructions.

How to convert GTFS to GIS shapefiles and KML

This tutorial will teach how you to convert any transit agency’s General Transit Feed Specification (GTFS) data into ESRI ArcGIS-compatible shapefiles (.shp), KML, or XML. This is simple to do because GTFS data is essentially a collection of CSV (comma separated values) text files (really, really large text files).

Note: I don’t know how to do the reverse, converting shapefiles or other geodata into GTFS data. I’m not sure if this is possible and I’m still investigating it. If you have tips, let me know.

Converting GTFS to GIS shapefiles

Instructions require the use of ArcGIS (Windows only) and a free plugin called ET GeoWizards GIS for any version of ArcGIS. I do not have instructions for Mac users at this time.

I wrote these instructions while converting the Chicago Transit Authority’s GTFS files into shapefiles based on a reader’s request. “Field names” are quoted and layer names are italicized.

  1. Download the GTFS data you want. Find data from agencies around the world (although not many from Europe) on GTFS Data Exchange.
  2. Import into ArcGIS the shapes.txt file using Tools>Add XY Data. Specify Y=lat and X=lon
  3. Using ET GeoWizards GIS tools, in the Convert tab, convert the points shapefile to polyline.
  4. Select the shapes layer in the wizard, then create a destination file. Click Next.
  5. Select the “shape_id” field
  6. Click the checkbox next to Order and select the field “shape_pt_sequence” and click Finish.
  7. Depending on the number of records (the CTA has 466,000 shapes), it may take a while.
  8. The new shapefile will be added to your Table of Contents and appear in your map.
  9. Import the trips.txt and routes.txt files. Inspect them for any NULL values in the “route_id” field. You will be using this field to join the routes and trips table. It may be a case that ArcGIS imported them incorrectly; the text files will show the correct data. If NULL values appear, follow steps 10 and 11 and continue. If not, follow steps 10 and 12 and continue. This happens because ArcGIS inspected some of the data and determined they were integers and ignored text. However, this is not the case.
  10. Export the text files as DBF files so that ArcGIS operates on them better. Then remove the text files from the Table of Contents.
  11. (Only if NULL values appear) Go into editing mode and fix the NULL values you noticed in step 9. You may have to make a new column with a more forgiving data type (string) and then copy the “route_id” column into the new column. Then continue to step 12.
  12. Join routes and trips based on the field “route_id” – export as trips_routes.dbf
  13. Add a new column to shapes.shp called “shape_id2”, with data type double 18, 11. This is so we can perform step 14. Use the field calculator to copy the values from “shape_id” (also known as ET_ID) to “shape_id2”
  14. Join routes_trips with shapes into routes_poly based on the field “shape_id” (and “shape_id2”)
  15. Dissolve routes_poly on “route_id.” Make sure all selections are cleared. Use statistics/summary fields: “route_long,” “route_url.” Save as routes_diss.shp
  16. Inspect the new shapefile to ensure it was created correctly. You may notice that some bus routes don’t have names. Since these routes are well documented on the CTA website, I’m not going to fill in their names.

Click on the screenshot to see various steps in the tutorials.

Converting GTFS to KML

After you have it in shapefile form, converting to KML is easy – follow these instructions for using QGIS. Or if you want to skip the shapefile-creation process (quite involved!), you can use KMLWriter, a Python script. Also, I think the latest version of ArcGIS has built-in KML exporting.

Converting GTFS to XML

If you want to convert the GTFS data (which are essentially comma-separated value – CSV – files) to XML, that’s easier and you can avoid using GIS programs.

  • First try Mr. Data Converter (very user friendly).
  • If that doesn’t work, try this website form on Creativyst. I tested it by converting the CTA’s smallest GTFS table, frequencies.txt, and it worked properly. However, it has a data size limit. (User friendly.)
  • Next try csv2xml, a command line tool. (Not user friendly.)
  • You can also use Microsoft Excel, but read these tips and caveats first. (I haven’t found a Microsoft application I like or think is user friendly.)

The importance of sharing data in KML format

The KML file is an important format in which to share locational data. KML was developed by a company called Keyhole, which Google purchased in 2004, and subsequently released Keyhole’s flagship product: Earth.

A Keyhole Markup Language file is a way to display on a map (particularly a 3D globe of Earth) a collection of points with a defined style. Google has added more functionality and style to the KML format, expanding the styles that can be applied and the information that can be embedded.

KML, like XML (eXtensible Markup Language), is extremely web-friendly. For a web application at work I developed, I included this PHP class that creates an KML file on-demand based on a predefined database query. The file contains locations and attributes of recently installed bike racks in Chicago. EveryBlock imports the file and its information into their location-based service, aggregating many news types around your block.

But a KML file is more important than being the native file for use within Google Earth. It’s an open source text file that can be manipulated by a number of software programs on any computer system on earth (or read on a printed page). It’s not encoded, like shapefiles, so I can read the file with my own mind and understand the data it would present in a compatible map viewer. I see lines of organized syntax describing points and polygons, listing their attributes in plain language.

Have you ever tried to see the “inside” of a shapefile? Only GIS programs can read them for you. KML provides data producers and consumers the opportunities to keep data open, available, and easy to use. We need locational data for our work, and we need tools to help us use it, not hide it.

Converting shapefiles and KML files

Google Earth Pro is a slightly more advanced version than the free edition of the popular satellite imagery application (okay, it does way more, but many people just use that feature). One major additional feature it includes is the ability to import GIS shapefiles and display their features on top of the imagery, including terrain. It’s useful to have your data as KML (Keyhole Markup Language) because KML (or KMZ) is easier to share and Google Earth standard edition is free. But then again, it’s useful to have your KML files as shapefiles because proper GIS software is more powerful at analyzing data. Also, someone might ask you for your data in shapefile format (but they could easily follow these instructions).

Good data management requires options. Options mean your data won’t be locked into a proprietary format. Data want to be free! Read on for ways to convert your KML and shapefile data:

Converting KML files to shapefiles

Like Google Earth Pro, Quantum GIS (QGIS) can convert KML or KMZ to shapefile, and best of all – it doesn’t cost $400 per year (it’s free!). QGIS is a cross-platform application meaning it will run on Windows, Mac OS X, and Linux.

Use QGIS to convert a KML or KMZ file to shapefile:

  1. Click on Layer > Add Vector Layer
  2. Find your KML or KMZ file.
  3. Right-click your new layer and click “Save as shapefile.”

Zonums provides online conversion tools. Or, use ArcGIS and this plugin to convert KML files to shapefiles.

Converting shapefiles to KML files

The freeware Shp2kml 2.o (Windows only) from Zonums will convert shapefiles to KML files. Want some free, interesting data to try it out? Check my ever expanding repository.

ESRI’s ArcGIS can convert KML files to shapefiles using this plugin and then import the shapefile as a layer onto your map.

Creating KML files online

As I described in this post, BatchGecode will generate a KML file for you by inputting a list of addresses and names. Additionally, Google Earth (part of the rising Google GIS platform) creates KML files. Google’s My Maps feature also allows you to generate KML files (for sharing or download) by clicking and drawing points and lines on a map and inviting you to describe the features you create. Use this to get a map of your church congregation, or a map of people who voted for your candidate.

GeoCommons Finder lets you upload geodata in many formats, save it to your profile, and then download it into multiple formats. You can upload a shapefile (.shp) and its accompany files (shx, dbf, and prj), verify that it read your data correctly,

More choices for converting

Additional software with conversion capabilities:

  • MapWindow (another free software choice; Windows only) – An alternative to QuantumGIS and ArcGIS.
  • ExpertGPS (Windows only, not free) – Ideal for GPS device owners, or for researchers using GPS devices in projects. But it can convert the GPS and shapefile data into KML, shapefiles, or a spreadsheet, amongst other functions.
  • Zonums, creator of the standalone Shp2kml software converter, now offers many online tools for KML users, including one that reverses the conversion and exports shapefiles from KML files. I found the link on
  • OpenGeo Suite – Commercial software with non-profit licenses.
  • uDig – Free GIS software, but I haven’t had good experiences with it on my computers.

GeoCommunity has a good article, with screenshots, on how some of these programs work.

Need to work with General Transit Feed Spec (GTFS) data?

Converting a transit agency’s GTFS to shapefile and GeoJSON with QGIS

Many years ago I wrote a tutorial on how to use an ArcGIS plugin to convert a transit agency’s GTFS package – a group of files that describe when and where their buses and trains stop – into files that could easily be manipulated by popular GIS desktop software.

That was so long ago, before I became an expert in using QGIS, a free and open source alternative to ArcGIS.

This tutorial will show you how to convert GTFS to a shapefile and to GeoJSON so you can edit and visualize the transit data in QGIS.


First you’ll need to have QGIS installed on your computer (it works with Linux, Mac, and Windows). Second you’ll need a GTFS package for the transit agency of your choice (here’s the one for Pace Suburban Bus*, which operates all suburban transit buses in Chicagoland). You can find another transit agency around the world on the GTFS Data Exchange website.

Section 1: Let’s start

  1. Open QGIS.
  2. Load your GTFS data into the QGIS table of contents (also called the Layers Panel). Click Layer>Add Layer>Add Delimited Text Layer. You will be adding one or two files depending on which ones are provided.

    QGIS add delimited text layer

    Add delimited text layer.

  3. Now, here it can get tricky. Not all transit agencies provide a “shapes.txt” file. The shapes.txt file draws out the routes of buses and trains. If it’s not provided, that’s fine, but if you turn them into routes based on the stops.txt data, then you will have funny looking and impossible routes.

    QGIs browse for the stops.txt file

    Browse for the stops.txt file

  4. Click on “Browse…” and find the “stops.txt”. QGIS will read the file very quickly and determine which fields hold the latitude and longitude coordinates. If its determination is wrong, you can choose a different “X field” (longitude) and “Y field” (latitude).
  5. Click “OK”. A new dialog box will appear asking you to choose a coordinate reference system (EPSG). Choose or filter for “WGS 84, EPSG:4326”. Then click “OK”.
  6. The Pace bus stops in the Chicagoland region are now drawn in QGIS!

    Pace bus stops are shown

    Pace bus stops are shown

  7. If the GTFS package you downloaded includes a “shapes.txt” file (that represents the physical routes and paths that the buses or trains take), import that file also by repeating steps 4 and 5.

Section 2: Converting the stops

It’s really easy now to convert the bus or train stops into a shapefile or GeoJSON representing all of those points.

  1. Right-click the layer “stops” in the table of contents (Layers Panel) and click “Save As…”.
  2. In the “Save vector layer as…” dialog box, choose the format you want, either “ESRI Shapefile” or “GeoJSON”. **
  3. Then click “Browse” to tell QGIS where in your computer’s file browser you want to save the file. Leave the “CRS” as-is (EPSG:4326).

    Convert the bus stops to a shapefile or GeoJSON.

    Convert the Pace bus stops to a shapefile or GeoJSON.

  4. Then click “OK” and QGIS will quickly report that the file has been converted and saved where you specified in step 3.

Section 3: Converting the bus or train routes

The “shapes.txt” file is a collection of points that when grouped by their route number, show the physical routes and paths that buses and trains take. You’ll need a plugin to make the lines from this data.

  1. Install the plugin “Points to Paths”. Click on Plugins>Manage and Install Plugins… Then click “All” and search for “points”. Click the “Points to Paths” plugin and then click the “Install plugin” button. Then click “Close”.

    Install the Points to Paths plugin.

    Install the Points to Paths plugin.

  2. Pace bus doesn’t provide the “shapes.txt” file so we’ll need to find a new GTFS package. Download the GTFS package provided by the Chicago Transit Authority, which has bus and rail service in Chicago and the surrounding municipalities.
  3. Load the CTA’s “shapes.txt” file into the table of contents (Layers Panel) by following steps 4 and 5 in the first section of this tutorial.  Note that this data includes both the bus routes and the train routes.

    QGIS load CTA bus and train stops

    Import CTA bus and train stops into QGIS

  4. Now let’s start the conversion process. Click on Plugins>Points to Paths. In the next dialog box choose the “shapes” layer as your “Input point layer”.
  5. Select “shape_id” as the field with which you want to “Point group field”. This tells the plugin how to distinguish one bus route from the next.
  6. Select “shape_pt_sequence” as the field with which you want to “Point order field”. This tells the plugin in what order the points should be connected to form the route’s line.
  7. Click “Browse” to give the converted output shapefile a name and a location with your computer’s file browser.
  8. Make sure all  of the options look like the one in this screenshot and then click “OK”. QGIS and the plugin will start working to piece together the points into lines and create a new shapefile from this work.

    These are the options you need to set to convert the CTA points (stops) to paths (routes).

    These are the options you need to set to convert the CTA points to paths (routes).

  9. You’ll know it’s finished when the hourglass or “waiting” cursor returns to a pointer, and when you see a question asking if you would like the resulting shapefile added to your table of contents (Layers Panel). Go ahead and choose “Yes”.

    QGIS: CTA bus and train points are converted to paths (routes)

    The CTA bus and train points, provided in a GTFS package, have been converted to paths (routes/lines).

  10. Now follow steps 1-4 from Section 3 to convert the routes/lines data to a shapefile or GeoJSON file.**


* As of this writing, the schedules in Pace’s GTFS package are accurate as of January 18, 2016. It appears their download link always points to the latest version. Transit schedules typically change several times each year. Pace says, “Only one package is posted at any given time, typically representing Pace service from now until a couple of months in the future. Use the Calendar table to see on which days and dates service in the Trips table are effective.”

** Choose GeoJSON if you want to show this data on a web map (like in Leaflet or the Google Maps API), or if you want to share the data on GitHub.

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:
// gather results
// query part for: “railway=subway”
/*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.

Converting shapefiles to GeoJSON, and other format conversions

To develop the Chicago Bike Map app, I had a problem I thought would be simple to solve: load train lines into a Leaflet-powered map. I had the train lines stored as a polyline shapefile but Leaflet can only read the GeoJSON format or a string of geographic coordinates representing lines.

I eventually found a solution (I can’t remember how) and I need to share it with you. The converter can do more than ESRI shapefiles to GeoJSON. It can reproject the data in the conversion. It can convert from several formats to several other formats.

The site is called MyGeodata Converter. You upload a ZIP file of geographic files – .shp and its companion files (.prj, .dbf, .shx), .kml, and .gpx. Let’s take the Chicago Transit Authority train lines shapefile straight from the City of Chicago’s open data portal. It downloads as a zipped collection of a shapefile and its buddies and we can take this file straight to the Converter and upload it. The Converter will unzip it and read the data; it will even identify the projection system (for Chicago-based geographic data, its common to use NAD83 Illinois StatePlane East FIPS 1201 Feet (SRID 102671, the same as SRID 3435).

The Converter will convert to one of the following formats, with same or new projection; accepts SQL statements to extract a subset of data:

  • ESRI shapefile
  • GML
  • KML, KMZ
  • GeoJSON
  • Microstation DGN
  • MapInfo File
  • GPX
  • CSV

BikeLock app based on dataset I opened up

Bike parking at Daley Plaza, downtown Chicago. 

It’s really cool to see work you did “go places”. A friend of mine who works at Groupon just linked me to an iOS app called BikeLock that finds bike racks near you on iPhones, iPads, and iPod touches. It’s based on bike rack location data in the City of Chicago’s Data Portal. (The data on there is old, while the data in the public API I built is real time.)

Download it from the iTunes Store for 99 cents. The developer is Mike Jahn, another Groupon staffer. You can get the same information for free, though, on my mostly mobile-friendly Can I bring my bike on Metra? web app, and a website I made for the Chicago Department of Transportation (CDOT).

A screenshot of the Can I bring my bike on Metra? bike rack finder website. 

That data comes straight from the Bike Parking Web Application I started developing in 2008 soon after I started working in the Chicago Bicycle Program. It was good that my supervisor had the same perspectives I did about open and transparent data and work. But it didn’t start like that; here’s the full story:

My first job at the Bicycle Parking Program was to deal with abandoned bikes, get them off the street. I was taught the existing method of keeping track of my work, but I used my programming skills (in PHP, MySQL, and with the Google Maps API) to develop a web application that tracked it faster and mapped out the abandoned bikes I had to visit and tag with a notice. I was using this for a few days or few weeks and then show my boss. His reaction was something like, “Great! Now make one for bike racks!”

Why? Well, let’s take this quote from Judy Baar Topinka, Illinois comptroller, speaking Tuesday about her office’s new website, The Ledger, which lists the state’s unpaid bills among other financial data.

“The object of the exercise is to make everything that we know of in the comptroller’s office public. If we know it, you’ll know it.” WBEZ

I made one for bike racks. I created two environments, one for private administration at the office (“Bike Parking Web Application”) and one for the public (“public interface”). A later feature I added to the public interface was the Advanced Search. This allows you to filter by Ward, Community Area, and Status. You can then choose your sorting method. A map will appear above the results. You can download the results as either an XLS file, and XLS file that’s designed to be imported in GIS programs (like QGIS), or a KML file.

I’m aware of just one other app that uses this data set: I don’t know if MassUp uses the real-time API that my Metra bike rack finder uses.

Logan Square McDonald’s crash map

This is part of a series of articles on the issue of lifting the pedestrian street designation on a part of Milwaukee Avenue in Logan Square so that the McDonald’s franchise owner can demolish the building, build a new building, and build a double order point (“tandem”) drive through. Read the first post

At the hearing on December 13, 2011, Alderman Reilly asked if there was evidence of injuries or crashes due to the drive through. No one brought this data to the hearing. I cannot directly attribute the crashes to the existence of the drive through (unless I had the original crash reports), the drive through probably generates traffic that would not be there without the drive through, and it causes people to have to turn across a lane of traffic, either to enter the driveway on Milwaukee, or when exiting the driveway onto Sawyer, or when turning onto Milwaukee from Sawyer. I am looking for studies that research the impacts of drive throughs at fast food restaurants and pharmacies.

37 people were involved in 13 crashes within 100 feet of the center of the McDonald’s driveway from 2007-2010. Seven people were injured, one was a pedestrian. Double the search radius to 200 feet and we see 87 people involved in 35 crashes. Now, four pedestrians and cyclist were injured in addition to the 10 drivers and passengers injured.

Download the data in this map. View a larger map

This was my testimony at the zoning committee hearing (this may not be verbatim, but it’s really close):

Hello, my name is Steven Vance. I work as a consultant and writer on sustainable transportation advocacy and planning projects. The text amendment to modify the pedestrian street designation may negatively impact the continuity and safety in traffic of all modes along Milwaukee Avenue, which happens to be the city’s most popular bike route.

I ask that McDonald’s provide a traffic impact study before this matter is discussed further.

Lynn, a Logan Square neighbor, describes more of what happened at the hearing, as well as the next step at the Zoning Board of Appeals.

Here’s a map of all pedestrian streets in Chicago. View larger map.

Download a KML file of all the pedestrian streets. Download the shapefile of all the pedestrian streets. Thank you to Azad Amir-Ghassemi and Bill Vassilakis for their help in digitizing the table of pedestrian streets in the zoning code.

Update January 10, 2013

Driving danger

Crash data from the Illinois Department of Transportation show several crashes along Milwaukee Avenue from 2005 to 2011. If this location hadn’t been removed from the P-Street ordinance, McDonald’s would have been required to install both the drive-thru’s entrance and exit on Sawyer, where there is markedly less traffic than on Milwaukee (or not build them at all). This project has not only allowed a documented hazard to persist (despite the P-Street designation), but perhaps to be worsened.

From 2005-2011, there were 3 bike-automobile crashes and 5 pedestrian-automobile crashes within 200 feet of the drive-thru entrance, which includes the intersection of Sawyer and Milwaukee (where many people will drive back onto Milwaukee from the drive-thru exit). There were 82 car-car crashes in the same period. At a nearby intersection, Milwaukee/Dawson, an intersection with a similar retail makeup and traffic count, shows about half the number of crashes.

« Older posts

© 2016 Steven Can Plan

Theme by Anders NorénUp ↑