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To improve the urban transport planning and safety management, an approach is proposed to identify travel hotspots based on mobile phone data. The workflow including data processing, movement state recognition, computing of travel density, identification of travel hotpots and visualization is described. A case study is presented to test the proposed approach. Moreover, the spatial distribution change of travel hotspots by time internal is analyzed. The location differences of travel hotspots on weekdays and weekends are also identified accurately with thematic map. The result shows that the hotspot identification can locate spatial clustering of trip activities effectively. It indicates that this approach is a valuable supplementary way to make up for the deficiency of traditional field surveys. It can provide some significant information for unban transport management and planning.
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