Posted by: jdantos | February 22, 2012

Capital Bikeshare Data, Part 8: Mileage and Elevation Change

A quick part 8 showing elevation changes and station-to-station distances of all Capital Bikeshare trips in 2011.

I had previously noticed a fairly dominant Bikeshare market between residential neighborhoods north of Massachusetts Ave. and the downtown area.  In fact, trips between what I called Mid-City, Mid-City North, and downtown accounted for more than half of all Bikeshare trips. Corey had previously noticed that the higher up a station is, the more likely it is that originating trips are headed downhill.  That makes sense from a physics point of view – from a higher station, most destinations are downhill.  But, I think the question is whether the city’s topography is adding potentially costly imbalance to the system? Is there a relationship between the sender/receiver status of a station, and the mix of uphill vs. downhill trips from it?

From a long-term perspective, it’s okay for a station to be imbalanced over short periods of time, as a downtown station is receiver in the morning and a sender in the evening.  As long as those demand markets are numerically in balance, one solution is to just add more capacity (docks and bikes) to be sure that supply can accommodate demand.  But if a station is not in balance over the long haul, and consistently sees its docks fill or empty without natural re-balancing from other users, it will require constant attention and re-filling by the crews and the vans, which is (presumably) expensive.

Corey graciously provided the (straightline?) distances and elevation changes between all Bikeshare stations, which I ran a quick a frequency distribution on in Access on all trips in 2011.  The system is flowing net downhill.  The re-balancing vans appear to be moving bikes uphill, on net.  60% of all trips are headed downhill (or level), and 40% are headed uphill. I put “net zero” trips in the downhill section, but these are

Capital Bikeshare is flowing slightly net downhill. 6% more trips went downhill than uphill (net, station-to-station).

The vast majority of trips do not go up or down more than 20 meters, or about 60 feet.  This may be because it’s difficult to cover much more elevation change on a short bike ride in Washington, but it is possible – some O-D pairs can involve as much as 80-100 meter change.

Of course, we only know the elevation of the station where the customer began and ended, not the actual elevation change they pedaled.  I think about this on my commute sometimes, as I glide down Capitol Hill towards downtown, only to pedal uphill again from the Mall.

So, the question is whether some stations are imbalanced because of topography, and if so, how badly.  Is there a consistent relationship between a station’s “balancedness” and the average elevation change of trips originating from it?  I did up a quick scatter plot, although I’m still not sure whether it’s answering the question:

"Balancedness" vs. Average Elevation Change in Capital Bikeshare stations, all trips 2011

To me, this chart is saying a few things, although I’m not sure of the right way to visualize this data (let me know if you want the source file to play with and re-display):

  • The majority of stations were roughly in balance in 2011.  The big cluster of stations in the middle are stations where origins didn’t exceed destinations by much, and just as many trips went uphill as downhill over the course of the year.
  • Topography and demand does seem to be causing imbalance at some stations, and the problem is primarily “sender” stations where trips mostly flow downhill – e.g. the top left quadrant.  The stations in this area are, to name a few, 16th & Harvard NW, 36th & Calvert NW, 14th & Harvard NW, Wisconsin & Macomb NW, Tenleytown, 11th & Kenyon NW.
  • High-elevation stations are not necessarily imbalanced. Topography is not the only thing causing imbalance.  Look at the circles spread out along the x-axis – these are high elevation stations where most originating trips are headed downhill, but the are similar numbers of trips coming back uphill dock and balance out the station over the year.
By the way, that station where the net trip was uphill by 50 meters? Minnesota Ave. & Nannie Helen Burroughs NE – but only 4 trips originating in 2011 (it was only installed very recently, I believe).
What am I missing on this one? I’m not quite sure this one is there yet… anyone have any ideas?

Finally, here’s one last nugget – a distribution of station-to-station trip distances, all trips in 2011.  Of course we can’t tell the actual path people followed from origin to destination,but  these numbers are coming out similar to the duration numbers:

Station-to-station distance of Capital Bikeshare trips, all trips 2011. About half of all trips are 1.5 miles or less, and 83% are less than 3 miles - about the distance one can bike in under the 30-minute window of free time.

A few observations:

  • Lots of short trips! Half of all trips are 1.5 miles or less. This is consistent with the finding of lots of rentals in the 10-15 minute time frame.
  • There is no big difference between casual and registered users’ trip distances, and the majority (83%) are under 3 miles – also about what you can reasonably bike in the 30-minute window.
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Responses

  1. I think the Nannie Helen Burroughs station is one of the original DC stations, but it’s been out of service for almost a year (construction?), so not too much data to go by.

  2. [...] Next in a series of posts mining crowd-sourced Capital Bikeshare data. This one does a simple correlation between temperature and usage. If you’re really bored, see also parts 1, 2, 3, 4, 5, 6,7, and 8. [...]

  3. [...] usage by a few dimensions. Check out parts 2, 3, 4, 5, 6, 7 (maps of travel patterns), 8, [...]

  4. [...] on system-level usage by trip duration. See parts 1, 3, and 4, 5, 6, 7 (maps of travel patterns), 8, [...]

  5. [...] focuses on net “balanced-ness” across the system. See also parts 1, 2, 3, 4, 5, 6, 7, 8, [...]

  6. [...] Capital Bikeshare data. This one maps a bunch of data by station. See also parts 1, 2, 3, 4, 5, 6, 8, and [...]

  7. I have cruiser with no speeds, so any elevation is killer for me, what’s the best resource for bicycling elevation within the city?

    • Lisa – try the (relatively new) bikeplanner.org – just drag the target in the bottom left towards “F” for flat when planning a route, and it should minimize elevation change for you. Let me know how it goes!

  8. [...] less. Using bike sharing, a walker could easily extend to longer trips. This Capital Bikeshare data analyzed by JD Antos shows that 83% of trips are under three miles, and up to seven miles – an order of magnitude [...]


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