CFlow: A Novel High-Order Flow Analysis Unit for Detecting Spatiotemporal Mobility Patterns Based on Origin-Destination Data
文献类型：期刊论文
| 作者 | Xin, Rui1,2; Yang, Kuan1; Yang, Jian3; Li, Tingting3; Wang, Jiaoe2 |
| 刊名 | TRANSACTIONS IN GIS
 |
| 出版日期 | 2025-05-01 |
| 卷号 | 29期号:3页码:e70065 |
| 关键词 | collective mobility flow cruise taxis high-order flow analysis unit OD pairs online taxis spatiotemporal mobility pattern |
| ISSN号 | 1361-1682 |
| DOI | 10.1111/tgis.70065 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Mobility behavior research has long been a focal point in geographic information science (GIS). Many researchers use isolated OD pairs as flow analysis units when studying mobility behavior based on OD (origin-destination) data. However, isolated OD pairs only reflect individual mobility, which may constrain applying a collective analytical perspective, hampering the exploration of the potential value of OD data. In this research, we investigate combining isolated OD pairs in close spatiotemporal proximity to form aggregated edges and introduce a novel high-order flow analysis unit, collective mobility flow (CFlow), for mining spatiotemporal mobility patterns. Compared to traditional OD research, CFlow provides richer contextual information by weaving together spatiotemporal proximity OD pairs. Such transformation has leveraged the sequence-based data structure that empowers OD analysis with more intelligent tools. Furthermore, this paper designs relevant indicators for CFlows to analyze its spatiotemporal characteristics, including time span and area coverage. In particular, we apply classical frequent pattern mining algorithms to CFlows to explore frequently occurring collective spatiotemporal mobility patterns. To evaluate the effectiveness of the proposed CFlows extraction and analysis framework, extensive experiments have been carried out using OD data from cruise taxis and online taxis in Xiamen, China. Experiment results reveal spatiotemporal variations in CFlows under the two taxi operational modes, taxis seeking passengers and passengers seeking taxis, validating the feasibility of the proposed methods. The proposed CFlow analysis methods enable the discovery of spatiotemporal mobility patterns in long-term spatiotemporal interactions, thus enriching the modeling toolset for a comprehensive understanding of spatiotemporal interactions in OD data. |
| URL标识 | 查看原文 |
| WOS研究方向 | Geography |
| 语种 | 英语 |
| WOS记录号 | WOS:001499360000008 |
| 出版者 | WILEY |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/214652]  |
| 专题 | 区域可持续发展分析与模拟院重点实验室_外文论文 |
| 通讯作者 | Xin, Rui; Yang, Jian |
| 作者单位 | 1.Shandong Univ Sci & Technol, Coll Geodesy & Geomat, Qingdao, Peoples R China; 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China; 3.Informat Engn Univ, Sch Geospatial Informat, Zhengzhou, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xin, Rui,Yang, Kuan,Yang, Jian,et al. CFlow: A Novel High-Order Flow Analysis Unit for Detecting Spatiotemporal Mobility Patterns Based on Origin-Destination Data[J]. TRANSACTIONS IN GIS,2025,29(3):e70065. |
| APA | Xin, Rui,Yang, Kuan,Yang, Jian,Li, Tingting,&Wang, Jiaoe.(2025).CFlow: A Novel High-Order Flow Analysis Unit for Detecting Spatiotemporal Mobility Patterns Based on Origin-Destination Data.TRANSACTIONS IN GIS,29(3),e70065. |
| MLA | Xin, Rui,et al."CFlow: A Novel High-Order Flow Analysis Unit for Detecting Spatiotemporal Mobility Patterns Based on Origin-Destination Data".TRANSACTIONS IN GIS 29.3(2025):e70065. |
入库方式： OAI收割
来源：地理科学与资源研究所
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