Category: Information

What abysmal pavement quality on a brand new bike lane means

January 4, 2013 / / 16 Comments

Approaching the intersection and bike lane minefield. 

I find it very embarrassing that Chicagoans are supposed to ride their bicycles in this. I feel embarrassed riding my bike in this. I rode my bike on this pavement of abysmal quality and then felt ashamed and uncomfortable that I exited the bike lane and rode elsewhere.

The bike symbol succumbs to flooding which occupies half the bike lane’s width. 

I felt like a person in a wheelchair given an “accessible” theater seat behind a column that blocks a majority of my view of the stage. I felt like I was a reporter at a newspaper given a new computer where the keyboard was missing 42 keys. The bike lane was unusable, I was the butt of a cruel joke. This felt like a pittance, throwing crumbs to the masses.

2013 April Fool’s Day came early, in fall 2012. 

The photos in this post show a bike lane in Douglas Park against the curb, with a painted buffer, running in a minefield of patches and potholes on asphalt pavement. The bike lane was installed in the fall of 2012, as part of Mayor Emanuel’s efforts to construct 100 miles of protected bike lanes. The goal has since been reduced after the definition of a protected bike lane was surreptitiously changed. The change was revealed by Grid Chicago.

You can find this at the intersection of Sacramento Boulevard and Douglas Boulevard in Lawndale on the Near Southwest Side of Chicago. View more photos of this and the other West Side Boulevards bike lanes on my Flickr. They’ve probably been the most controversial: there were complaints because of ticketing cars parked in the under construction bike lane on Marshall Boulevard; then there were complaints about the “decreased safety” of the protected bike lane on Independence Boulevard which has prompted CDOT to agree to remove it and replace it with a buffered bike lane. The Independence Boulevard debacle started because of ticketing cars parked in the under construction bike lane – I doubt it would have become an issue if cars weren’t ticketed.

Franklin Boulevard at Kedzie Avenue, taken on the same day. Thankfully it’s wide enough that you can bike around it while still being in the bike lane. 

Mapping guns in your town: is that okay?

December 25, 2012 / / 6 Comments

This screenshot shows the pistol permit holders in Westchester County, New York. The highest density of permit holders appears to be at the border with Bronx County, also known as the northern edge of New York City. 

An ABC News story I read through the Yahoo! News website tells about The Journal News, covering Westchester (Yonkers, New Rochelle) and Rockland (New City, Pomona) counties in New York, posting the names and addresses, on a map, of gun permit owners. The map contains:

…the addresses of all pistol permit holders in Westchester and Rockland counties. Each dot represents an individual permit holder licensed to own a handgun — a pistol or revolver. The data does not include owners of long guns — rifles or shotguns — which can be purchased without a permit. Being included in this map does not mean the individual at a specific location owns a weapon, just that they are licensed to do so. [Notice that some dots are outside the county.]

This article is interesting to me for two reasons:

1. The article has hyperlinks to the (alleged?) Facebook profiles of two people who commented on The Journal News’s website. I predict this will only become more common. I don’t have a Facebook profile to link to.

2. The rationale to make a map seems reasonable: so people know where there are potentially guns in their neighborhood. It seems reasonable that people want to know where there are potential sources of danger and harm near them.

The names and addresses were obtained through “routine” (their words, not mine, but it is pretty routine and normal) Freedom of Information Act (FOIA) requests. The quantity and types of guns are not considered to be public record, although this may not be true, according to the ABC News article.

Free high resolution maps of Chicago on which to draw

November 28, 2012 / / 0 Comments

For a Grid Chicago article I was writing, I wanted to draw on a map to demonstrate to readers where people were commuting and not commuting. I wanted the map to show CTA lines. I didn’t want to use a Google Maps screenshot because it would have been low resolution, and I didn’t think the styling would be appropriate.

I opened up TileMill and whipped up my own maps! I already had the base layers set up for the Chicago Bike Map app, so I duplicated that project and then added the Chicago Transit Authority and Metra train lines with data and styles prepared by OpenPlans (created for its Chicago bike sharing Shareabouts installation; download the data and styles here). Highways, the most common geographic reference point in cities, are also included on the map.

Data comes from OpenStreetMap contributors and the styling is OSM-Bright.

Go grab them on Flickr. Use them as needed but please provide attribution to “Steven Vance, OpenPlans, and OpenStreetMap contributors”.

Chicago map, with Metra

Chicago map, with CTA

Chicago map, with CTA and Metra

Converting shapefiles to GeoJSON, and other format conversions

November 12, 2012 / / 0 Comments

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

Finding a new way to measure cities’ bike friendliness in the United States, part 2

November 5, 2012 / / 0 Comments

One of the reasons I developed my own bike friendly city ranking system was to provide a better measurement when comparing cities. Since the League of American Bicyclists (LAB) uses a nominal ranking (Platinum, Silver, Gold, Bronze), the difference in bike friendliness between cities of the same rank may be small or great. A numerical scoring system on a predictable and familiar scale will better highlight the distance of one city to another on achieve that city’s level of bike friendliness.

I created a method that would compare my ranking to LAB’s ranking and that was to find the variance (which isn’t the same as range) in scores in my ranking for each nominal level in LAB’s ranking. Platinum cities had a very high variance and Bronze cities had the lowest variance. Gold and Silver had swapped positions: Gold cities had a lower variance than Silver cities.

The beauty with creating your own bike friendly measurement system is that you can make the outcome order whatever you want.

In the days since, I’ve developed another bike friendliness measurement system, one that’s easier to understand, whose rankings are still relative to other cities, and that can be weighted. (I’m emphasizing the bike commute mode share.) It uses percentile scoring so all scores are positive but still based on the distribution of values. I’ve listed the scores for Method 1 (which uses a normalizing function based on mean and standard deviation) and Method 2 below.

[table id=5 /]