Abstract
As the smartphone market grows, tracking a person’s own positions become easier and popular. Especially for the bicycling, file based GPS data make it easier to manage and access personal trajectories. In this paper, we propose an effective color coding method for massive bicycle trajectories visualization. The motivation of the method is based on characteristics of the bicycle trajectories which have different spatial aspects compare to the automobiles. The proposed method modifies the color of the line segments based on the direction and flow, and provides visually enhanced trajectories. GPS data collected from Han riverside bicycle tracks were applied to the proposed visualization methods, and shown the potential possibilities for trajectory analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Garmin. http://www.garmin.com/us/
Dill J, Gliebe J (2008) Understanding and measuring bicycling behavior: a focus on travel time and route choice. OTREC-RR-08-03 final report
Caulfield B, Brick E, McCarthy OT (2012) Determining bicycle infrastructure preferences—a case study of Dublin. Transp Res Part D-Transp Environ 17(5):413–417
Buehler R, Pucher J (2011) Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes. Transportation 39(2):409–432
Agamennoni G, Nieto JI, Nebot EM (2011) Robust inference of principal road paths for intelligent transportation systems. IEEE Trans Intell Transp Syst 12(1):298–308
Brunsdon C (2007) Path estimation from Gps tracks. In: The 9th international conference on geocomputation. National University of Ireland, Maynooth
Hauser H, Lampe OD (2011) Interactive visualization of streaming data with kernel density estimation. In: Proceedings of IEEE pacific visualization symposium
Scheepens R, Willems N, van de Wetering H, Andrienko G, Andrienko N, van Wijk JJ (2011) Composite density maps for multivariate trajectories. IEEE Trans Vis Comput Graphics 17(12):2518–2527
Zheng Y, Wang L, Zhang R, Xie X, Ma WY (2008) GeoLife: managing and understanding your past life over maps. In: Proceedings of the 9th international conference on mobile data management. IEEE Press, Beijing pp 211–212
Acknowledgments
This research is supported by Ministry of Culture, Sports and Tourism(MCST) and Korea Creative Content Agency(KOCCA) in the Culture Technology(CT) Research & Development Program
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Lee, D., Kim, J., Choi, H., Hahn, M. (2013). Color Coding for Massive Bicycle Trajectories. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_60
Download citation
DOI: https://doi.org/10.1007/978-94-007-5860-5_60
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5859-9
Online ISBN: 978-94-007-5860-5
eBook Packages: EngineeringEngineering (R0)