C07

Research Abstracts on Spatial Information ScienceCSIS DAYS 2013

Spatio-Temporal Analysis of Bicycle Commuting Behavior in the Greater Tokyo Area
Using a Micro-Scale Persontrip Database
Konstantin Greger1, Yuji Murayama21
筑波大学大学院 生命環境科学研究科 空間情報科学分野, 2 筑波大学 生命環境科学研究科 空間情報科学分野
連絡先: <greger@geoenv.tsukuba.ac.jp> Web: <http://www.konstantingreger.net/>
total, 2.4 times each in average. Overall they usedtheir bicycles for a total distance of 478,738 km.
The average distance was 4.2 km per person.
We focused specifically on the morning rush hour
period from 6:00am to 9:59am. Overall, 68,029
people used their bikes during those 4 hours, thatequals 60.6% of the total cyclist population. They
got on their bikes 1.1 times on average. Overall theyused bicycles for 154,279km, which results in an
average distance of 2.3km per person.
A detailed analysis of the multi-modal use ofvarious means of transportation during the morning
rush hour also revealed interesting insights: Trips bybicycle during the morning rush hour go mostly(63%) all the way from home to the final destination.
When integrated into a multi-modal trip, bicycles
are mostly used on the “home”-end of the trip.
Finally, a spatio-temporal analysis showed that theusage of bicycles during the morning commute
differs greatly by location, depending onsocio-demographic factors, urban structural function,
special infrastructures. Figure 1 shows the numberof bicycle subtrips ending within each OD zone (theareal unit used in the underlying data and also in ourresearch). The relationship between the ends ofbicycle subtrips and railway stations with large
passenger volumes is easily noticeable. This
relationship will be the main focus of our future
research.

(1) Motivation: Within the realm of transportation
research in Japan bicycle traffic is heavily
underrepresented. This is especially true for the fieldof transport geography. Yet, the need for mobility
under the constraints of highly urbanized areas,
bicycles are an attractive alternative means oftransportation, that deserve a closer inspection.
(2) Originality: The aforementioned scarcity ofgeographical research about bicycle traffic in Japan
makes this study one of the first of its kind. In
addition, the state-of-the-art analysis of themicro-scale persontrip database fits well the trend
for the analysis of big data.
(3) Approach: Since this project has only been started
recently we are still in an early stage of descriptive
data analysis. To do this we employed the excellent
Tokyo Persontrip Database (PFlow) by the Tokyo
Metropolitan Area Transportation Planning Council(東京都市圏交通計画協議会) and the Center for
Spatial Information Science, the University ofTokyo (CSIS, 東京大学空間情報科学研究センター). It contains detailed information about 587,340
individuals synthesized to 1-minute positions. This
results in 845,769,600 point positions in total, which
we converted into a PostgreSQL database.
(4) Results: In total 112,286 people used their bikes
during the sample period (24 hours), which equals
19.1% of the total sample population of 587.334
people. They got on their bikes 272,897 times inFig. 1:
Absolute number ofbicycle subtrips in
the West of Tokyo,
ending within each
OD zone and their
spatial relationshipwith train stations,symbolized by their
daily passenger
volume.

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