Journal of Geo-information Science ›› 2017, Vol. 19 ›› Issue (8): 1011-1018.doi: 10.3724/SP.J.1047.2017.01011

• Orginal Article • Previous Articles     Next Articles

A Multi-scale Visualization Method for the Trajectory Origin-Destination Data

JIN Cheng1,3(), CHEN Yuanyuan2, YANG Min4,5,*()   

  1. 1. Information Engineering University, Zhengzhou 450001, China
    2. Institute of Remote Sensing & Geographical Information System, Peking University, Beijing 100871, China
    3.Xi′an Research Institute of Surveying and Mapping, Xi’an 710054, China
    4. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China
    5. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, China
  • Received:2017-01-05 Revised:2017-05-17 Online:2017-08-20 Published:2017-08-20
  • Contact: YANG Min;


Based on the taxi trajectory data from the city of Beijing, this study proposes a multi-scale visualization approach for trajectory OD (Origin-Destination) data. First, we extract OD points from initial trajectory raw data eliminating invalid points. Then, the distribution space of OD data is subdivided by density analysis and administrative unit aggregation. Finally, we define relevant parameters to summarize inherent OD flow pattern and customize their presentation of multi-scale visualization. In the process above, three regionalization results, which correspond to block level, business district level and district level, are obtained by setting different values of the minimal area of the aggregated region. Therefore, representations at three different scales can be outputted. The experimental results confirmed that our method could effectively achieve the reduction of trajectory big data and reveal mobility pattern, which is helpful for future decision making.

Key words: trajectory data, multi-scale visualization, flow pattern, clustering and regionalization