ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-2, 173-179, 2016
https://doi.org/10.5194/isprs-annals-III-2-173-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
02 Jun 2016
BIG BICYCLE DATA PROCESSING: FROM PERSONAL DATA TO URBAN APPLICATIONS
C. J. Pettit, S. N. Lieske, and S. Z. Leao City Futures Research Centre, The University of New South Wales, Sydney , Australia
Keywords: Big data, little data, data processing, data visualisation Abstract. Understanding the flows of people moving through the built environment is a vital source of information for the planners and policy makers who shape our cities. Smart phone applications enable people to trace themselves through the city and these data can potentially be then aggregated and visualised to show hot spots and trajectories of macro urban movement. In this paper our aim is to develop procedures for cleaning, aggregating and visualising human movement data and translating this into policy relevant information. In conducting this research we explore using bicycle data collected from a smart phone application known as RiderLog. We focus on the RiderLog application initially in the context of Sydney, Australia and discuss the procedures and challenges in processing and cleaning this data before any analysis can be made. We then present some preliminary map results using the CartoDB online mapping platform where data are aggregated and visualised to show hot spots and trajectories of macro urban movement. We conclude the paper by highlighting some of the key challenges in working with such data and outline some next steps in processing the data and conducting higher volume and more extensive analysis.
Conference paper (PDF, 878 KB)


Citation: Pettit, C. J., Lieske, S. N., and Leao, S. Z.: BIG BICYCLE DATA PROCESSING: FROM PERSONAL DATA TO URBAN APPLICATIONS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-2, 173-179, https://doi.org/10.5194/isprs-annals-III-2-173-2016, 2016.

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