Tag: data

Measuring gas prices and bicycling trips

From the Chicago Tribune: Gas prices continued to rise Monday, driven higher for nearly two weeks straight by the turmoil in Libya, with analysts expecting prices to keep climbing.

Active Transportation Alliance asks, “How can we make the gas price bubble permanent?” -Essentially the same topic I write about below.

I was thinking ever since I first read in the Chicago newspapers that gas will hit $4 per gallon this year (it already has in the City) that there’s a relationship between the price of gas and the number of people on bicycling or the number of trips people make on their bicycles.

As the price of gas rises, so does the number of people out bicycling on the streets. As the price of gas falls, bicycling declines as well.

Chart from GasBuddy.com showing average gas prices in Chicago for the past 3 years.

The data available to us doesn’t necessarily support this hypothesis, but the data available* is nearly worthless. Gas prices were over $4 per gallon in 2008. That was when Chicago started seeing tons of people on the street on their bicycles. The local Fox News affiliate interviewed Mike Amsden, a city planner at the Chicago Department of Transportation (CDOT), about the bike counts (first in five years) in a news segment about the influence of $4.65 and a “major peak, almost 350% in pedal pushers this year.”

Several newspapers published articles about the palpable increase in cycling, including a Time Out issue called “Bike Love” with messenger Jeff Perkins on the cover and interviewing 7 local cyclists inside. All of them published “how to get out and ride”-type articles. But despite the many new riders on the street in 2008, few came back the next year!

This graphic describes my point about gas prices up, bike trips up; gas prices down, bike trips down (but perhaps ending at a rate a little higher than where it started).

2009 came and the gas prices dropped – the modern heyday of Chicago cycling was gone. 2008 saw the highest numbers at 2 of 3 locations also counted in 2003, although the difference in study months makes the comparison suspect. I hope that 2011 is the start of annual and accurate counts of bicycling in Chicago.

But it’s reasonable to expect that some of the new people riding their bikes instead of taking expensive car trips will stick with it the following year, even as gas prices decline. Let’s keep these riders bicycling year after year, encouraging more to stay on the bike path than would normally otherwise with strategies like more urban-appropriate infrastructure (separated and protected bike lanes; secure bike parking at workplaces and train stations; traffic calming/slower traffic) as well as enforcement of laws that protect cyclists.

Let’s concentrate less on the “insane”  numbers of people cycling on Milwaukee Avenue at Ohio Street (3,121 bikes on September 15, 2009) and more on how to raise the number of people cycling on our other streets. Milwaukee Avenue doesn’t need anymore attention (except for its intersections). Getting people off Milwaukee and safely and efficiently onto east-west and north-south routes should be the priority. -Photo shows Halsted/Grand/Milwaukee, just 300 feet southeast of the Ohio count location.

*Available data

The American Community Survey (ACS) 3-year estimate for 2006-2008 tells us that 1.0% of working Chicagoans 16+ took their bikes to work (nevermind the tinny sample size that makes this data near worthless – it’s the only thing we have*). The 3-year estimate before (2005-2007) says 0.9% took their bikes to work. Not much of a peak or increase! For 2007-2009, the data shows 1.1% cycled to work.

Also ignore the fact that the ACS only asks about the mode you spent the most distance on. It does not collect data on multi-mode trips. So if you bike 3 miles to the train and the train is 30 miles to your destination, the ACS would only record “public transportation.”

Free online GIS tools: An introduction to GeoCommons

Read my tutorial on how I created the pedestrian map with GeoCommons. Read on for an introduction to GeoCommons and online GIS tools.

GeoCommons, like Google My Maps and Earth, is part of the “poor man’s GIS package.” It’s another tool that provides (few) of the functions that desktop GIS software offers. But it excels at making simple and somewhat complex maps.

I first used GeoCommons over a year ago. I started using it because it would convert whatever data you uploaded into another format that was probably more useful. I mentioned it in this article about converting files. For example, if you have a KML file, you can upload it and export it as a shapefile for GIS programs, or a CSV file to load into a table editor or spreadsheet application.

After creating the Chicago bike crash maps using Google Fusion Tables, I wanted to try out another map-making web application, one that provided more customization and prettier maps.

I found that web application and created a version of the bike crash maps, with several other data layers, in GeoCommons. I overlaid bike counts and bikeways so you can observe some relationships between each visual dataset. My latest map (screenshot below), created Wednesday, shows pedestrian counts in downtown Chicago overlaid with CTA and downtown Metra stations, as well as the 48 intersections with the most pedestrian collisions (from this UNC study, PDF).

Screenshot of pedestrian count map described above.

How these online GIS tools can be useful to you

I bet there’s a way you can use Google Fusion Tables and GeoCommons for your job or project. They’re extremely simple to use: they can take in data from the spreadsheets you’re already working on and turn them into themed reference maps. With mapping, you can do simple, visual analysis that doesn’t require statistical software or knowledge.

Imagine plotting your client list on a map and grouping them by age to see if perhaps your younger clients tend to live in the same neighborhoods of town, or if they’re more diverse (should you do this, keep the map private, something that you can’t do in GeoCommons – yet).

You may also find it useful if you want to create a route for your salespeople or for visiting church members at their homes. Plot all the addresses on a map, then manually filter them into different groups based on the clusters you see. With Google Fusion Tables, you can easily add a new column with the GROUP information and apply a numbered or lettered group and then re-sort.

Other things you can do in GeoCommons

  • Merge tables with geography – I uploaded two datasets: a table containing census tract IDs and demographic information for Cook County I downloaded from the American FactFinder 2; and a shapefile containing Cook County census tracts boundary information. After merging them, I could download a NEW shapefile that contained both datasets.
  • Make multi-layer maps
  • Symbolize based on frequency/rate
  • Convert data – This is by far the most useful feature. It imports “shapefiles (SHP), comma separated values (CSV), Keyhole Markup Language (KML), and GeoRSS” and exports “Shapefile, CSV, KML, GeoRSS Atom, Spatialite, and JSON” (from the GeoCommons user manual).

Read my tutorial on how I created the pedestrian map with GeoCommons.

You asked for it, you got it – Chicago bike count data

Note: This post doesn’t have any analysis of the data or report, nor do I make any observations. I think it’s more significant to hear the ideas you have about what you see in the map or read in the data.

A lot of people wanted the Chicago bike crash and injury data overlaid with bike counts data.

In 2009, Chicago Department of Transportation (CDOT) placed automatic bike counting equipment at many locations around the city. It uses pneumatic tubes to count the number of bicyclists (excludes cars) at that point in the street – it counts ALL trips, and cannot distinguish between people going to work or going to school. This is dissimilar from Census data which asks respondents to indicate how they go to work.

Well, good news for you! CDOT today released the bike counts report from data collected in 2009 (just in time). There has been overwhelming response about the bike crash map I published – this shows how rabid the public is for information on their environments (just yesterday someone told me that they switched bike routes based on the crash frequency they noticed on their original route).

The size of the blue dot indicates the bicycle mode share for that count location. Mode share calculated by adding bikes and cars and dividing by bikes.

Get the data

A photo of the EcoCounter counting machine in action on Milwaukee Avenue (this was taken during testing phase, where CDOT compared automatic and manual counts to determine the machine’s accuracy).

How to use this map:

  1. Find a blue dot (count location) in an area you’re interested in.
  2. Zoom into that blue dot.
  3. Click on the blue dot to get the number of bikes counted there.
  4. Then observe the number of purple dots (crashes) near that count location.

What do you see that’s interesting?

What else is coming?

Now let’s hope the Active Transportation Alliance and the Chicago Park District release their Lakefront Trail counts from summer 2010. CDOT may have conducted bicycle counts in 2010 as well – I hope we don’t have to wait as long for that data.

I hope to have a tutorial on how to use GeoCommons coming soon. You should bug me about it if I don’t post it within one week.

Photos of Chicago bike commuters by Joshua Koonce.

Bike crash map in the press

Thank you to the Bay Citizen, Gapers Block, and the Chicago Bicycle Advocate (lawyer Brendan Kevenides). They’ve all written about the bike crash map I produced using Google Fusion Tables. And WGN 720 AM interviewed me and aired it in April 2011.

View the map now. The map needs to be updated with injury severity, a field I mistakenly removed before uploading the data.

The Bay Citizen started this by creating their own map of bike crashes for San Francisco, albeit with more information. I had helped some UIC students obtain the data from the Illinois Department of Transportation for their GIS project and have a copy of it myself. I quickly edited it using uDig and threw it up online in an instant map created by Fusion Tables.

A guy rides his bicycle on the “hipster highway” (aka Milwaukee Avenue), the street with the most crashes, but also has the most people biking (in mode share and pure quantity).

Why did I make the map?

I made this project for two reasons: One is to continue practicing my GIS skills and to learn new software and new web applications. The second reason was to put the data out there. There’s a growing trend for governments to open up their databases, and your readers have probably seen DataSF.org’s App Showcase. But in Chicago, we’re not seeing this trend. Instead of data, we get a list of FOIA requests, or instead of searchable City Council meeting minutes, we get PDFs that link to other PDFs that you must first select from drop down boxes. But both of these are improvements from before.

I would love to help anyone else passionate about bicycling in Chicago to find ways to use this data or project to address problems. I think bicycling in Chicago is good for many people, but we can make it better and for more people.

Read the full interview.

Why did women in Chicago stop bicycling to work? And other stories about data

Why did women in Chicago stop bicycling to work?
Or is our data unreliable?

Showing relative cycling-to-work rates between 2005 and 2009 in Chicago. Data from table S0801 in American Community Survey, 1-year estimates. Read the comments on this post for why this is not the best data source – 3-year estimate shows same decline in women cycling to work.

Note: The sample size is puny – data was collected from 80,613 housing units in Illinois. I don’t know how many of those were in Chicago (and we have 1,063,047 housing units). The American Community Survey only collects data on transportation modes to work for ages 16 and up.

But we simply have no other data! Maybe the Chicago Metropolitan Agency for Planning can release the Chicago data they collected for the 2008 household travel survey to show us bicycling rates for all trip purposes (they divided the report into counties). The sample size would still be small, but we could compare the work rates to find some support between the datasets.

We should look into how New York City counts bicycling as an additional way to gauge trends in Chicago (it has limitations of geography and area).

They conduct two types of counts. The first is the screenline count for bridges, Staten Island Ferry, the Hudson River Greenway, and all Avenues at 50th Street. They do this three times per year. Then, seven more times a year, they count at the same places (except the Avenues) from April to October.

While this data does not give them information on who cycles in the boroughs, it does give them a good indicator of cycling levels in Manhattan. It also disregards trip purpose, counting everyone going to work, school, or for social activities.

Sidenote: The New York Police Department will begin making monthly statistical reports on bicycle crashes in the city.