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Big Data and Cycling
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DOI：10.1080/01441647.2015.1084067.png)
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摘要
En 中文
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.
Keyword:
Cycling
Big data
bike mobility
bikeshare
spatial analysis
GPS
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9.9
论文数:
1.5K
被引数:
6.4K
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Mining bicycle sharing data for generating insights into sustainable transport systems挖掘自行车共享数据，以深入了解可持续交通系统
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