standard Analyzing Bike Sharing Demand with GIS

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The New York City Department of Transportation (DOT) recently released its report on the background work that went into bike-share station siting decisions.  The first Citi Bike stations were installed earlier this month in New York City and eventually hundreds of stations will be built around the city.  The first phase of the fee-based bike sharing calls for 293 bike stations.  Ultimately, the bike sharing system will have 600 stations and 10,000 bikes, making it the largest in North America.

Under the bike sharing program, users can sign up for annual, weekly, or daily rates that allow them to borrow a bike from one location and return it at the bike station closest to their destination.  Users can rent bikes for an unlimited amount of time but can only check out a single bike for a maximum of 30 minutes (for the annual and weekly passes) and 45 minutes for the annual pass before overtime charges are incurred.

To study the best citing of those bike stations, NYC DOT used maps and geospatial analysis on a variety of levels.  DOT held 159 public bike share meetings where planning maps were discussed and also collected over 10,000 station location suggestions via its interactive bike station planning map which has been archived here.  Individual maps were provided to stakeholders to review and help narrow down from 2,881 options to the final 600 locations where bike share stations would be placed.  Maps formed a integral part of the public participation process with workshop participants marking on planning maps both positive and negative input about potential bike station locations.

Those interested can access an online map of the bike station locations or access PDFs showing detail at the neighborhood scale.

Planning map with marked comments from one of the many public outreach meetings for New York City's bike share program.

Planning map with marked comments from one of the many public outreach meetings for New York City’s bike share program.

GIS was also used not only to synthesize the massive amount of public and organizational input on bike station locations but to also create a predictive model for sizing each bike share station.  In order to undersize the number of bike racks needed for each location, a number of factors were used to create a model of bike trips across the city.  The model for generating number of bike strips along each street looked at the neighborhood land use (residential, commercial, parkland, schools, etc.), population, transit use (based on board and alighting for buses and subway turnstile counts).  NYC DOT also used data from the  Taxi and Limousine Commission (TLC) which provided GPS data from taxi cabs showing origins and destinations of trips.  The model generated estimates on the number of bike trips in a 24 period for each street segment.

Predictive GIS model for the number of bike trips within a 24-hour period for New York City.

Predictive GIS model for the number of bike trips within a 24-hour period for New York City.

In 2012, Alexander Rixey with Fehr & Pehrs published a report entitled, “Station-Level Forecasting of Bike Sharing Ridership: Station Network Effects in Three U.S. Systems” which utilized modeling using QGIS and ArcGIS toolsets to look at “effects of demographic and built environment characteristics near bike sharing stations on bike sharing ridership level.”



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