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Geographical Stacking Point Map of Staying Points

  • Jing He
  • , Haonan Chen
  • Tsinghua University
  • China University of Mining & Technology, Beijing

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Regardless of the size of the study, the trajectory contains many behaviors of moving objects in dynamic and complex environments. The advent of modern computing and software environments for integrating and manipulating trajectory data has become an important driver of mobile object trajectory research. However, understanding the behavior of moving objects is still an indirect task, as it involves not only the decision process, but also space, time, attribute constraints, and context. Therefore, the development of characterization and computational frameworks that facilitate analysis and exploration of the trajectory state of moving objects is still considered a research challenge. In this paper, we introduce a semantic behavior that expresses the trajectory stop points by the visualization technique of stacked points, in order to find a better ability to predict how trajectories respond to environmental changes and how these responses are related in time and space.

源语言英语
主期刊名2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020
出版商Institute of Electrical and Electronics Engineers Inc.
73-79
页数7
ISBN(电子版)9781728141114
DOI
出版状态已出版 - 5月 2020
已对外发布
活动5th IEEE International Conference on Big Data Analytics, ICBDA 2020 - Xiamen, 中国
期限: 8 5月 202011 5月 2020

出版系列

姓名2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020

会议

会议5th IEEE International Conference on Big Data Analytics, ICBDA 2020
国家/地区中国
Xiamen
时期8/05/2011/05/20

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