TagAmerican Community Survey

How many cars are in Rogers Park?

There are a gazillion cars in Rogers Park, and there’s no place to park them. That’s the declaration you would gather if you listen to “Lakefront Car Tower” (a parking garage) proponents, including the 49th ward alderman, Joe Moore.

The parking problem is so bad in Rogers Park that a parking garage at Sherwin Avenue and Sheridan Road that would provide less than 100 overnight parking spaces to the public was actually sent from Asphaltia, the god of car parks. It’s so bad that “[m]any car owners find themselves stuck in their home at night” – yes, the alderman really published that on his website – because they find a parking space on Friday night and can’t move the car until Monday morning. The horror of using your feet, pedals, the bus, the train, car sharing, paratransit, or a Segway!

(I’d love to get into parking pricing policy now, but I’ll just leave you with this: of course there is going to be a demand problem when the supply of publicly-owned on-street parking costs $0 per year.)

This post is actually a tutorial on how to use United States Census data to find how many cars are in the neighborhood of Rogers Park, not a laugh about Asphaltia’s teachings.

Let’s begin! Continue reading

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

A really smart person could come up with a way to measure day-to-day bike friendliness based on how well cities adhere to standards that keep roads clear of obstructions that further frustrate the commute, like construction projects that squeeze bikes and cars together. 

I work at home. There are some days when I only leave my house to get milk from the Mexican grocery store at the end of my block (which makes awesome burritos). That means I ride my bike half as much as people who commute to work. on their bikes. Today I had a bunch of errands to run: drop off stuff, buy stuff, take pictures of stuff for my blog, Grid Chicago.

It was a very frustrating experience. I don’t need to go into details about how I was harassed by people who the state so graciously awarded a license to drive. But it happened. And it happens a hundred times a day to people cycle commuting in Chicago. I got to thinking about “bike friendly” cities. Is there a way to incorporate driver attitudes in there? I tweeted:

[tweet_embed id=264575958374305792]

Later I had the idea to use some very simple but objective measurements to create a new bike friendliness metric. It would help ensure that “Silver” (a ranking the League of American Bicyclists [LAB] uses) in one city means the same as “Silver”. It can expand from here but basically it works like this:

  • The share of people going to work who go by bike is a proxy for how “friendly” a city is to biking.
  • If a city has a lot of people biking to work, it must be friendly.
  • If a city has a few people biking to work, it must be non-friendly.
  • Cities are compared to each other to determine friendly and non-friendly.
  • The metric uses standard deviation to score cities.

Stop me if this has already been done.

I created a spreadsheet that lists the top 10 populous cities in the United States. I then added 10 more cities: Austin, Boston, Davis, Madison, Minneapolis, Portland, San Francisco, Seattle, and Washington, D.C. In the next column I listed their bike commute share from the American Community Survey 2006-2010 5-year estimates. I calculated the standard deviation and mean of these shares and then in another column used Apple Numbers’s STANDARDIZE function:

The STANDARDIZE function returns a normalized value from a distribution characterized by a given mean and standard deviation.

I think that’s what I want. And the output is close to what I expected. I then found the LAB ranking for each city and found the variance of each ranking to see how far apart each city within one ranking was from another city in the same ranking. The results were interesting: the higher the ranking, the more variance there was.

Hurricane Sandy prompted a lot of New Yorkers to bike. It made headlines, even. Photo by Doug Gordon. 

I wanted to add another metric of bike friendliness, and that’s density. To me, a higher density of people would mean a higher density of places to go (shop, eat, learn, enjoy) and friends and family would be closer, too. Or the possibility of meeting new people nearby would be higher. Yeah, I’m making a lot of assumptions here. So I applied the STANDARDIZE function there as well. I added this number to the previous STANDARDIZE result and that became the city’s score.

So, in this new, weird ranking system, the most bicycle friendly cities are…drum roll please…

  1. Davis, California (Platinum)
  2. New York City (Silver) *
  3. San Francisco (Gold) *
  4. Boulder (Platinum)
  5. Boston (Silver)
  6. Philadelphia (Silver)
  7. Tie: Chicago*, Washington, D.C. (Silver)
  8. Tie: Portland* (Platinum), Minneapolis* (Gold)

Remember, I said above that any author of a list should spend at least a day cycling in each city. I’ve starred the cities where I’ve done that – I’ve cycled in 5 cities for at least a day.

I only calculated 20 cities. Ideally I’d calculate it for the top 50 most populous cities AND for every city that’s been ranked by LAB.

LAB cities list (PDF). My spreadsheet (XLS).

Stats from the OECD: Comparing traffic injuries of the United States and Netherlands

For an article I’m writing for Architect’s Newspaper about the Chicago Forward CDOT Action Agenda, I wanted to know about traffic injuries and fatalities in the United States, but compared to the Netherlands and Denmark and other places with a Vision Zero campaign (to have 0 traffic deaths each year).

I already knew the OECD had a good statistics database and web application. With a few clicks, I can quickly get a table of traffic injuries (casualties) listing just the countries I want. I can easily select the years I want, too.

In one more click the web application will show a time animated bar chart. A feature I’d like to see added is dividing the figure (in this case traffic injuries) by the population. Check out the video to see what it looks like. The United States looks to be in terrible shape, but our country has several times more residents.

I had trouble downloading and opening the CSV file of the data table I created. The XLS file was damaged, also. The built-in Mac OS X Archive Utility app couldn’t open the .gz file, but I used The Unarchiver app successfully.

My calculations, based on data from OECD (national population and traffic fatalities), Illinois Department of Transportation (IDOT), and the American Community Survey:

Fatalities per 100,000 in 2009

  • United States: 11.02472
  • Denmark: 5.48969
  • Netherlands: 4.35561
  • Sweden: 3.84988
  • Chicago: 16.74891
  • United Kingdom: 3.83555

Chicago’s fatality rate per 100,000 citizens in 2009 was 16.75 (473 deaths on the roads). The fatality rate dropped in 2010: just 11.65 deaths per 100,000 residents (315 deaths on the roads; the population also decreased).

Updated September 28, 2012, to add the United Kingdom. 

Introduction to DIY bike ridership research

A lot of people ask me how many people are out there bicycling.

“Not a lot”, I tell them.

And I explain why: the primary source of data is the American Community Survey, which is a questionnaire that asks people questions about how they got to work in a specific week. (More details on how it does this below.) We don’t have data, except in rare “Household Travel Surveys”, about trips by bike to school, shopping, and social activities.

It’s comparable across the country – you can get this data for any city.

Here’s how:

  1. Visit the “legacy” American FactFinder and select American Community Survey, operated by the United States Census Bureau.
  2. Select 2005-2009 American Community Survey 5-Year Estimates (or the latest 5-year estimate). This is the most accurate data.
  3. In the right-side menu that appears, click on “Enter a table number”.
  4. In the new window, input the table number ” S0801″ (“Commuting Characteristics by Sex”) and submit the form. The new window will close and the other window will go to that table.
  5. Now it’s time to select your geography. In the left-side menu, under “Change…” click on “geography (state, county, place…)”
  6. In the window to change your geography, select “Place” as your “Geographic Type”.
  7. Then select the state.
  8. Then select your city and click “Show Result”.
Notes:
  • This data shows all modes people take to work, who live in that city. It’s highly probable that people are leaving the city to their jobs on these modes. For example, someone who lives in Rogers Park may ride their bike to work in Evanston.
  • The URL is a permanent link to this dataset. Each city has a unique URL. You should save these as bookmarks so you can easily reference the data later.
  • The question on the survey doesn’t allow multiple choices: “People who used more than one means of transportation to get to work each day were asked to report the one used for the longest distance during the work trip”.

Commuting rates in Chicago – a conversation

I had this conversation last night with a friend from Chicago. Enjoy. Data is from the American Community Survey, Table S0801. If you were to rate how much we bike, from a “typical Chicagoan’s” point of view, he would be “eccentric” and I would be “psychotic.”

Photo by Joshua Koonce.

Me
A friend of mine in Europe asked for bicycle commuting statistics for Chicago.
Man, the numbers were sad.

Friend
No shit.

Me
if we look at the 3-year estimates for work trips, then it’s
-2005-2007: 0.9%
-2006-2008: 1.0
-2007-2009: 1.1

Friend
Chicago is also a gigantic, sprawling modern city of hundreds of square miles and wide roads designed for masses of cars.

Me
And if we look at the 1-year estimates, which Matt argued on my blog are useless, it’s
-2005: 0.7%
-2006: 0.9
-2007: 1.1
-2008: 1.0
-2009: 1.1
The 3-year estimate has a MOE of ±0.1 so essentially, it could mean no change from year to year.
And the 1-year estimate has a MOE of ±0.2, so again, it could mean no change from year to year
UGH

Friend
Comparatively, old European cities don’t have a lot of bandwidth for autos and have density where people take short trips.
That’s still probably two or three times the distance people in Copenhagen or Cambridge or Amsterdam.

Me
So let’s say 50% of trips are 5 miles or less, and 25% of trips are 2.5 miles or less.
Yet 1% of all trips are taken by bike
If we could just DOUBLE that, it would be a miracle
The Bike 2015 Plan’s goal is to have 5% of all trips under 5 miles by bike.

Friend
That’s an ambitious goal.

Me
We don’t have any baseline data to show how many trips under 5 miles in 2006, at the inception of the Bike 2015 Plan, are by bike. In the end, we’ll never know if our ambitious goal was attained!

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.

Some disjointed thoughts about bike commuting rates and how we get them

  1. In November 2010, I wrote that Minneapolis and St. Paul, Minnesota, have a higher percentage of workers (16 and older) commuting to work by bicycle.
  2. Yesterday, I updated an article about how the frequency of women in Chicago bicycling to work is decreasing.
  3. Today, I started updating the November Minnesota article to include the 2007-2009 3-year estimates from the American Community Survey (which shows that bicycling to work is growing faster in Minneapolis than Chicago). View the rudimentary spreadsheet. Bottom line: MPLS jumped from 3.55% bike mode share to 4.14% and Chicago only went from 1.04% to 1.13% (but again, only counting employed people!). Can we get some recession job statistics?
  4. Unemployment rate in Minneapolis-St. Paul-Bloomington, MN-WI MSA is 6.5%; Chicago-Joliet-Naperville, IL-IN-WI MSA is 9.0%. See the table on Bureau of Labor Statistics.

But now I must pause and look at what I’m analyzing.

Someone pointed out in the comments on Chicago bicycling (and working) women that the sample size is low and the margin of error high meaning it’s hard to make accurate interpretations of the change in ridership from year to year. He suggested increasing the sample size.

Add this to the fact that the Census Bureau only collects data on trips to WORK and not everywhere else that people go daily. In this recession, fewer people are working. In fact, perhaps women lost their jobs more frequently than men. That could perhaps explain the drop in women bicycling to work. To increase the number of women bicycling to work, perhaps we just need to find more jobs for women. See points 3 and 4 above for evidence on the number of people who bicycle for transportation that we’re not counting.

After thinking these things over, my point is that gauging a city’s ridership based on Census Bureau home to work data is insufficient.

If these Phoenix bike riders aren’t going to work, they aren’t being counted.

To move from a bicycle subculture to a bicycle culture, we’ll need to know when we get there. We need a better picture on who is riding and for what purpose. CMAP rarely performs their household transportation survey (which gathers data on all trips on all modes and in many counties) and when they do, they don’t single out cities. In essence, Chicago doesn’t know where or why people are riding their bicycles (except for the limited and noisy information the Census or American Community Survey provides) – we have no good data!

Both New York City, New York, and Portland, Oregon, methodically perform bicycle counts annually. Both cities also count ridership on their bridges: Portland has at least 5 to count, NYC has over 10 (also called a screenline count). They can report how many people are riding bikes on the street, blind to their trip purpose and destination. It’s easy to note changes in ridership when you count all trips over work trips.

Frequency of Chicago women riding their bikes to work is down

UPDATE: I added data from years 2005-2007 to complement existing 2008-2009 data in Table 1 as well as a visual representation. I have also added data from the 3-year estimates to Table 2.

UPDATE 01/20/11: Added the most recent 3-year estimate that the Census Bureau released in January 2011 to Table 2.

In September 2009, I wrote about “what the Census tells us about bicycle commuting” and a couple of days ago I compared Chicago to Minneapolis and St. Paul.

I want to update readers on the changes between the 1-year estimate data reported in that article (from 2008) and the most recent 1-year estimate data (from 2009). Percentages represent workers in the City of Chicago aged 16 and older riding bicycles to work.

Table 1 – Bicycling to work, 16 and older, 1-year estimates

Year Total MOE Male MOE Female MOE
2005 0.7% +/-0.1 0.9% of 621,537 +/-0.2 0.4% of 541,013 +/-0.1
2006 0.9% +/-0.2 1.2% of 645,903 +/-0.3 0.7% of 563,219 +/-0.2
2007 1.1% +/-0.2 1.4% of 656,288 +/-0.3 0.7% of 574,645 +/-0.2
2008 1.0% +/-0.2 1.5% of 657,101 +/-0.3 0.5% of 603,640 +/-0.2
2009 1.1% +/-0.2 1.8% of 651,394 +/-0.3 0.4% of 620,350 +/-0.1

View graph of Table 1. MOE = margin of error, in percentage points.

We should be concerned about the possible decrease in the percentage of women riding bicycles to work, especially as the population size increased. The margin of error also decreased, thus suggesting an improvement in the accuracy of the data. There have already been many discussions (mine, others) as to why it is important to encourage women to ride bicycles and also what the woman cycling rate tells us about our cities and policies. If the decrease continues we must discover the causes.

But Table 1 doesn’t tell the full story.

As Matt points out in the comments below, the number of surveys returned for 1-year estimates is smaller than that from the Decennial Census. Therefore, I took a look at the two 3-year estimates available, each having a larger sample size than the 1-year estimates (see Table 2). The data below seem to show the opposite change than seen in Table 1: that the number of women bicycling to work has increased. The crux of our quandary is sample size. The sample size is the number of people who are asked, “How did this person usually get to work LAST WEEK?”

Table 2 – Bicycling to work, 16 and older, 3-year estimates

Click header for data source 2005-2007 2006-2008 2007-2009
Total workers 1,203,063 1,230,809 (+2.31%) 1,291,709 (+4.71%)
Males bicycling to work 7,549 9,014 (+19.41%) 11,014 (+18.16%)
Females bicycling to work 3,474 3,741 (+7.69%) 3,542 (-5.62%)

The number of discrete females who bike to work has decreased in the most recent survey (2007-2009) while the total number of workers 16 and older has increased, giving females bicycling to work a smaller share than the previous survey (2006-2008). We must be careful to also note the margin of error for females bicycling to work is ±499.

Matt suggested that sustainable transportation advocates “push for higher sampling” to reduce “data noise” and increase the accuracy of how this data represents actual conditions. I agree – I’d also like more data on all trips, and not just those made to go to work. Household travel surveys attempt to reveal more information about a region’s transportation.

One of the two overall goals of the Bike 2015 Plan is “to increase bicycle use, so that 5 percent of all trips less than five miles are by bicycle.” Unfortunately, the Plan doesn’t provide baseline data for this metric, but we can make some inferences (there will probably be no data for this in 2015, either). The CMAP Household Travel Survey summary from 2008 says that the mean trip distance (for all trips) for Cook County households is 4.38 miles (under five miles). The same survey says that for all trips, 1.3% were taken by bike. These can be our metrics. *See below for men/women breakdown. Note that no data for “all trips” exists for the City of Chicago.

We will not achieve the Bike 2015 Plan goal unless we do something about the conditions that promote and increase bicycling. Achieving the goals in the Bike 2015 Plan is not one group or agency’s responsibility. The Plan should be seen as a manifestation of what can and should be done for bicycling in Chicago and we all have a duty to promote its objectives.

Please leave a comment below for why you think the rate of women who bike to work has stayed flat and decreased, or what you think we can do to change this. Does it have to do with the urban environment, or are the reasons closer to home?

*The same survey also said: Cook County males used the bike for 1.9% of all trips. Cook County females used the bike for 0.8% of all trips.

Table 1 data comes from the 1-year estimates from the American Community survey, table S0801, Commuting Characteristics by Sex for the City of Chicago (permalink), which is a summary table of data in table B08006. Table 2 data directly from American Community Survey table B08006.

How many people ride bikes in Minneapolis and St. Paul compared to Chicago?

I applied for a job on Tuesday in the Minneapolis/St. Paul area (Twin Cities).

I had heard that more people, as a percentage of all commuters, commute by bike in Minneapolis and St. Paul than in Chicago and many other cities. If you’ve been reading Steven can plan for a while, you know that I visited Minneapolis in September 2009 and rented a bike for 24 hours.

I used the American FactFinder to get the details. And now I know what I heard is true.

Chicago Minneapolis St. Paul
Workers over 16 1,230,809 190,814 131,798
Ride bikes to work 12,755 6,770 1,567
Bike mode share 1.04% 3.55% 1.19%

Permalink to data results. Data from the 2006-2008 3-year American Community Survey estimates, table B08301.

Knowing these figures led me to question the nothing that Chicago is a bicycle-friendly city. If it’s so friendly to riding a bicycle, how come there aren’t more people riding their bikes to work?

One of my ideas: There are many trails criss-crossing Hennepin and Ramsey Counties that go to and through major neighborhoods and employment centers. These are essentially bike highways without the threat of a automobiles.

What the Census says about bicycle commuting

UPDATE 11-08-10: I wrote a post comparing the commuting statistics between Chicago, Minneapolis, and St. Paul.

UPDATE 02-12-11: Added 2009 data.

Prompted by this entry on BikePortland about the rise of bicycle commuting and the bicycle mode share in Portland, Oregon, I decided to research what the American Community Survey says about the mode share of bicycles as part of commuting where I live: Chicago. I’ll also post bicycle’s share of commuting for other locales, as well.

Some definitions, first:

  • Commuting means travel to and from work – the Census Bureau calls this “MEANS OF TRANSPORTATION TO WORK.” The Census Bureau does not collect information on travel to shopping, medical services, and other places in the decennial census or the yearly American Community Survey (which will supposedly replace the decennial census).
  • Block means the smallest area for which the Census Bureau reports statistics. Any smaller and the possibility that someone could personally identify you from the responses increases. Find your block. The American Community Survey reports information for much larger areas: In some cases, researchers can only select data at the county level. The Census Bureau provides information for the City of Chicago and other municipal divisions of many counties in Illinois.
  • Subject definitions. These describe the question asked to participants and include clarifying information in the case the participant doesn’t understand the question, or their answer is complex. Download the subject definitions for the 2008 American Community Survey.
  • Margin of error (MOE) means the high and low end of confidence. Read more about margin of error on the Census Bureau’s website.

For the American Community Survey, I found table S0801, Commuting Characteristics by Sex. In the decennial census, I found table  P30. MEANS OF TRANSPORTATION TO WORK FOR WORKERS 16 YEARS AND OVER. If you want to check my research, look for these tables of sample data.

Chicago:
Margin of error for male and female categories varied. Combined always reported 0.2%.

  • 2009 – 1.1% travel to work by bicycle. 1.8% male (MOE: 0.3%), 0.4% female (MOE: 0.1%). Workers over 16: 1,271,744. Permalink.
  • 2008 – 1.0% travel to work by bicycle. 1.5% male (MOE: 0.3%), 0.5% female (MOE: 0.2%). Workers over 16: 1,260,741. Permalink.
  • 2007 – 1.1% travel to work by bicycle. 1.4% male (MOE: 0.3%), 0.7% female (MOE: 0.2%). Workers over 16: 1,230,933. Permalink.
  • 2006 – 0.9% travel to work by bicycle. 1.2% male (MOE: 0.3%), 0.7% female (MOE: 0.2%). Workers over 16: 1,209,122. Permalink.
  • 2005 – 0.7% travel to work by bicycle. 0.9% male (MOE: 0.1%), 0.4% female (MOE: 0.1%). Workers over 16: 1,162,550. Permalink.

United States:
Margin of error happened to be the same for each reported category (combined, male, female).

  • 2009 – 0.6% travel to work by bicycle. 0.8% male, 0.3% female. MOE: 0.1%. Workers over 16: 138,591,804 (decrease). Permalink.
  • 2008 – 0.5% travel to work by bicycle. 0.8% male, 0.3% female. MOE: 0.1%. Workers over 16: 143,995,967. Permalink.
  • 2007 – 0.5% travel to work by bicycle. 0.7% male, 0.2% female. MOE: 0.1%. Workers over 16: 139,259,684. Permalink.
  • 2006 – 0.5% travel to work by bicycle. 0.6% male, 0.2% female. MOE: 0.1%. Workers over 16: 138,265,905. Permalink.
  • 2005 – 0.4% travel to work by bicycle. 0.6% male, 0.2% female. MOE: 0.1%. Workers over 16: 133,091,043. Permalink.

Read the BikePortland article if you want to know that Portland has a higher share of commuters traveling by bicycle than Chicago has.

And what about my block? As I mentioned above, we can only find information at the block group level in the decennial census. I live in Block Group 1 of Census Tract 6009 in Chicago, Illinois. I didn’t live here in 2000, though, the last time the decennial census occurred. Back then, out of 168 workers over 16, 4 of them rode their bikes to work! That equals .024% of the worker population in my block group. Oddly, though, the Census Bureau reported 946 people living in this Block Group. Looking at table P8 (Sex By Age), I see that 674 have at least 16 years of age. 178 people have at least 55 years. Does this mean a lot of people in the Block Group didn’t work at the time of the survey in 2000? I don’t know. Permalink to data.

By far, though, driving alone won as the most popular way to get to work: 71.423% of the worker population.

© 2014 Steven Can Plan

Theme by Anders NorenUp ↑