太阳成8722(中国)有限公司-GREEN NO.1

标题：Integrating algebraic multigrid method in spatial aggregation of massive trajectory data

作者： Siying Wang, Yunyan Du, Chen Jia, Meng Bian & Teng Fei*

来源出版物：International Journal of Geographical Information Science   DOI：10.1080

摘要：The advanced technologies in location-based services and telecom have yield large volumes of trajectory data. Understanding these data effectively requires intuitive yet accurate visual analysis. The visual analysis of massive trajectory data is challenged by the numerous interactions among different locations, which cause massive clutter. This paper presents a new methodology for visual analysis by integrating algebraic multigrid (AMG) method in data aggregation. The non-parametric method helps to build a multilayer node representation from a graph which is extracted from trajectory data. The comparison with AMG and other methods shows that AMG method is more advanced in both the spatial representation and the importance of nodes. The new method is tested with real-world dataset of cell-phone signalling records in Beijing. The results show that our method is suitable for processing and creating abstraction of massive trajectory dataset, revealing inherent patterns and creating intuitive and vivid flow maps.

文献类型：Research Article

语种：English

关键词：Spatial aggregation; trajectory visualization; algebraic multigrid; key node identification

通讯作者地址：

Fei, T (reprint author), School of Resource and Environmental Science, Wuhan University, Wuhan, China.

电子邮件地址： feiteng@whu.edu.cn

地址：

[Siying Wang, Chen Jia, Meng Bian & Teng Fei] School of Resource and Environmental Science, Wuhan University, Wuhan, China.

[Yunyan Du] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic sciences and natural Resources Research, CAS, Beijing, China.

影响因子： 2.370

全文链接：https://doi.org/10.1080/13658816.2018.1512713