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Article

Estimation of Hourly Link Population and Flow Directions from Mobile CDR

1
Human Centered Urban Informatics, Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
2
Remote Sensing of Environment and Disaster, Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(11), 449; https://doi.org/10.3390/ijgi7110449
Received: 27 September 2018 / Revised: 7 November 2018 / Accepted: 14 November 2018 / Published: 17 November 2018
The rise in big data applications in urban planning and transport management is now widening and becoming a part of local government decision-making processes. Understanding people flow inside the city helps urban and transport planners build a healthy and lively city. Many flow maps are based on origin-and-destination points with crossing lines, which reduce the map’s readability and overall appearance. Today, with the emergence of geolocation-enabled handheld devices with wireless communication and networking capabilities, human mobility and the resulting events can be captured and stored as text-based geospatial big data. In this paper, we used one-week mobile-call-detail records (CDR) and a GIS road network model to estimate hourly link population and flow directions, based on mobile-call activities of origin–destination pairs with a shortest-path analysis for the whole city. Moreover, to gain the actual population size from the number of mobile-call users, we introduced a home-based magnification factor (h-MF) by integrating with the national census. Therefore, the final output link data have both magnitude (actual population) and flow direction at one-hour intervals between 06:00 and 21:00. The hourly link population and flow direction dataset are intended to optimize bus routes, solve traffic congestion problems, and enhance disaster and emergency preparedness. View Full-Text
Keywords: big data; CDR origin–destination pairs; shortest-path analysis; hourly link population and flow direction; home-based magnification factor (h-MF) big data; CDR origin–destination pairs; shortest-path analysis; hourly link population and flow direction; home-based magnification factor (h-MF)
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MDPI and ACS Style

Lwin, K.K.; Sekimoto, Y.; Takeuchi, W. Estimation of Hourly Link Population and Flow Directions from Mobile CDR. ISPRS Int. J. Geo-Inf. 2018, 7, 449. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi7110449

AMA Style

Lwin KK, Sekimoto Y, Takeuchi W. Estimation of Hourly Link Population and Flow Directions from Mobile CDR. ISPRS International Journal of Geo-Information. 2018; 7(11):449. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi7110449

Chicago/Turabian Style

Lwin, Ko K., Yoshihide Sekimoto, and Wataru Takeuchi. 2018. "Estimation of Hourly Link Population and Flow Directions from Mobile CDR" ISPRS International Journal of Geo-Information 7, no. 11: 449. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi7110449

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