The public now has access to bikesharing data from a new city. Bixi Montreal has released a chunk of data from a day of bikesharing, which I’ve incorporated into my Trip Visualizer.
Montreal’s bikesharing system is the largest in North America, with 410 stations. Among the other systems I’ve studied – Washington D.C.’s Capital Bikeshare, the Boston Hubway, and the Minneapolis-St. Paul Nice Ride, it is the most heavily-used system.
Bixi dipped its toe into the “open data” pool by releasing a summary of trip history data for just a single day, good enough to get a first look at the system via the Bixi Montreal Trip Visualizer. That’s the same tool I used to visualize trip data for Washington, Boston, and the Twin Cities. There’s a new feature that comes in handy when trying to simplify the image that results from arrows stretching out from hundreds of points: the heat map shows the same data but in a smooth gradient.
This is also the first time the Visualizer lets you view subsets of data. Bixi released the day of data with two matrices: one for the A.M. and another for the P.M. A new option in the Visualizer lets you choose either set, or the two combined.
Now that we have data from four bikesharing systems, I thought I’d try to see how their statistics vary.
Bixi Montreal definitely has the greatest density of stations. There are many ways to measure the area covered by stations. I drew a “convex” polygon around the stations to get my estimate. Using that method, Montreal has about 3.6 stations per square kilometer. (When comparing numbers, bear in mind CaBi and Nice Ride cover multiple jurisdictions.) A more impartial measure of network density is to see how far it is to the closest station. Montreal also looks dense using those measurements:
System Sq km of region Stations Stations per sq km Average distance to closest station (meters) Bixi Montreal 115 sq km 410 3.6 271 m CaBi (Q4) 185 sq km 192 1.0 407 m Hubway 46 sq km 95 2.1 447 m Nice Ride 128 sq km 145 1.1 500 m
Living in Washington, I see Capital Bikeshare bikes so often I couldn’t imagine a busier system. But Montreal shows a system can support much higher levels of usage.
System Total trips Period Days Avg per day Stations Avg per station per day Bixi Montreal 19,643 une journée “typique” de semaine 1 19,643 410 48 CaBi Q4 475,736 Oct 1 – Dec 31, 2012 92 5,171 192 27 CaBi Q3 637,377 Jul 1 – Sep 31, 2012 92 6,928 189 37 Hubway 552,020 Jul 28 – Nov 30, 2011 Mar 15 – Oct 1, 2012 327 8,364 95 18 Nice Ride 273,999 Apr 2 – Nov 4, 2012 217 1,263 145 9
Solid conclusions are limited, since cycling is highly seasonal, and our data sets don’t come from the same date range. Plus, the cities vary by much more than just the number of stations. Each city has a different strategy when distributing stations. Do you place them where high bike traffic already exists, or do you place them where you want to encourage more bicycle usage?
I also wanted to compare the systems by looking at each system’s busiest station. It’s interesting that each system’s busiest station is about 5 times as active as that system’s average (ranging from 4.5 times to 5.4 times as big).
System Busiest station Trips from Days Avg per day % of system avg Bixi Montreal Métro Mont-Royal 258 1 258 538% CaBi Q4 Mass Ave & Dupont Circle NW 13,171 92 143 530% CaBi Q3 Mass Ave & Dupont Circle NW 18,116 92 197 532% Hubway South Station – 700 Atlantic Ave 26,555 327 81 450% Nice Ride IDS Center 10,570 217 49 544%
The systems have more in common when you look at average trip distance. The average trip ranges from 0.9 miles to 1.2 miles.
System Total trips Total distance travelled (meters) Average trip distance Bixi Montreal 19,643 37,464,347 m 1,907 m 1.2 mi CaBi Q4 475,736 841,302,940 m 1,768 m 1.1 mi CaBi Q3 637,377 1,127,093,457 m 1,768 m 1.1 mi Hubway 552,020 907,220,748 m 1,643 m 1.0 mi Nice Ride 273,999 413,984,261 m 1,511 m 0.9 mi
The busy stations do dominate the system, but it’s not quite as disproportionate as you might expect. In each system, half of the trips are generated by 17 percent to 25 percent of the stations, as shown in the table below. (Washington D.C.’s Metro subway system is in the same ballpark. Twenty-three percent of the stations generate 50 percent of the trips.)
System % of stations that generate 50% of all trips Bixi Montreal 25% CaBi Q4 21% CaBi Q3 21% Hubway 21% Nice Ride 17%
With bikesharing still in its infancy, having open data allows us to establish a baseline for how bikesharing systems operate.
One thing all bikesharing systems have in common is they all look beautiful when viewed on a map. I hope you’ll enjoy exploring the different cities in the Trip Visualizer.