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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Extracting Dynamic Urban Mobility Patterns from Mobile Phone Data
verfasst von : Yihong Yuan, Martin Raubal
Erschienen in: Geographic Information Science
Verlag: Springer Berlin Heidelberg
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The rapid development of information and communication technologies (ICTs) has provided rich resources for spatio-temporal data mining and knowledge discovery in modern societies. Previous research has focused on understanding aggregated urban mobility patterns based on mobile phone datasets, such as extracting activity hotspots and clusters. In this paper, we aim to go one step further from identifying aggregated mobility patterns. Using hourly time series we extract and represent the
dynamic mobility patterns
in different urban areas. A Dynamic Time Warping (DTW) algorithm is applied to measure the similarity between these time series, which also provides input for classifying different urban areas based on their mobility patterns. In addition, we investigate the outlier urban areas identified through abnormal mobility patterns. The results can be utilized by researchers and policy makers to understand the dynamic nature of different urban areas, as well as updating environmental and transportation policies.