RT Journal Article
T1 Big Data and cycling
A1 Zaltz-Austwick, Martin
A1 Ettema, Dick
A1 Kruijf, Joost De
A1 Romanillos Arroyo, Gustavo
AB Big Data has begun to create significant impacts in urban and transport planning. This paper covers the explosion in data-driven research on cycling, most of which has occurred in the last ten years. We review the techniques, objectives and findings of a growing number of studies we have classified into three groups according to the nature of the data they are based on: GPS data (spatio-temporal data collected using the global positioning system (GPS)), live point data and journey data. We discuss the movement from small-scale GPS studies to the ‘Big GPS’ data sets held by fitness and leisure apps or specific cycling initiatives, the impact of Bike Share Programmes (BSP) on the availability of timely point data and the potential of historical journey data for trend analysis and pattern recognition. We conclude by pointing towards the possible new insights through combining these data sets with each other – and with more conventional health, socio-demographic or transport data.
PB Taylor and Francis
SN 0144-1647
YR 2015
FD 2015-09-29
LK https://hdl.handle.net/20.500.14352/100723
UL https://hdl.handle.net/20.500.14352/100723
LA eng
NO Gustavo Romanillos, Martin Zaltz Austwick, Dick Ettema & Joost De Kruijf (2016) Big Data and Cycling, Transport Reviews, 36:1, 114-133, DOI: 10.1080/01441647.2015.1084067
DS Docta Complutense
RD 24 ago 2024