A multi-hierarchical method to extract spatial network structures from large-scale origin-destination flow data
文献类型：期刊论文
| 作者 | Zhou, Xingxing; Zhang, Haiping1; Ye, Xinyue2 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2024-01-08 |
| 关键词 | Spatial complex network spatial network structure map generalization spatial interaction intelligent optimization |
| DOI | 10.1080/13658816.2023.2301305 |
| 产权排序 | 2 |
| 英文摘要 | Extracting spatial network structure (SNS) from large-scale origin-destination flow data is an important approach for understanding interregional association patterns and interaction laws. Currently, the extraction of SNS primarily relies on complex network clustering or aggregated statistics with predefined regional constraints. However, these methods often overlook one or more fundamental principles essential for ensuring correctness and accuracy: 1) Aggregation of spatially proximate nodes is necessary when strong interactions exist, whereas separation is preferred in the absence of such interactions. 2) It is crucial to maintain strong interactions between non-spatially proximate nodes. 3) Ultimately, nodes within each group should exhibit spatial continuity. To address these challenges, a multi-hierarchical SNS extraction method is proposed, which focuses on raw node aggregating and generalization, measurement of interaction volume and strength between node groups and strategies for node/edge filtering. The effectiveness and value of the proposed method are demonstrated through a case study using city population migration data. Furthermore, the method provides a general approach for extracting SNSs from any origin-destination flow dataset that includes locations and weights, facilitating effective flow map generalization through aggregation of origin destination (OD) flow data. |
| WOS关键词 | REGIONS |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| WOS记录号 | WOS:001139050000001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201665]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Yangzhou Univ, Coll Informat Engn, Coll Artificial Intelligence, Yangzhou, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 3.Texas A&M Univ, Sch Architecture, College Stn, TX USA |
| 推荐引用方式 GB/T 7714 | Zhou, Xingxing,Zhang, Haiping,Ye, Xinyue. A multi-hierarchical method to extract spatial network structures from large-scale origin-destination flow data[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2024. |
| APA | Zhou, Xingxing,Zhang, Haiping,&Ye, Xinyue.(2024).A multi-hierarchical method to extract spatial network structures from large-scale origin-destination flow data.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE. |
| MLA | Zhou, Xingxing,et al."A multi-hierarchical method to extract spatial network structures from large-scale origin-destination flow data".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2024). |
入库方式： OAI收割
来源：地理科学与资源研究所
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