Length-squared L-function for identifying clustering pattern of network-constrained flows
文献类型：期刊论文
| 作者 | Fang, Zidong5,6; Shu, Hua4; Song, Ci5,6; Chen, Jie6; Liu, Xiaohan5,6; Jiang, Jingyu3,6; Jiang, Linfeng2,6; Liu, Tianyu5,6; Pei, Tao1,5,6 |
| 刊名 | INTERNATIONAL JOURNAL OF DIGITAL EARTH
 |
| 出版日期 | 2023-12-08 |
| 卷号 | 16期号:2页码:4191-4211 |
| 关键词 | Network-constrained flow clustering pattern network distance Ripley's K-function length-squared L-function |
| ISSN号 | 1753-8947 |
| DOI | 10.1080/17538947.2023.2265882 |
| 通讯作者 | Pei, Tao(peit@lreis.ac.cn) |
| 英文摘要 | The network-constrained flow is defined as the movement between two locations along road networks, such as the residence-workplace flow of city dwellers. Among flow patterns, clustering (i.e. the origins and destinations are aggregated simultaneously) is one of the cities' most common and vital patterns, which assists in uncovering fundamental mobility trends. The existing methods for detecting the clustering pattern of network-constrained flows do not consider the impact of road network topology complexity on detection results. They may underestimate the flow clustering between networks of simple topology (roads with simpler shapes and fewer links, e.g. straight roads) but with high network intensity (i.e. flow number per network flow space), and determining the actual scale of an observed pattern remains challenging. This study develops a novel method, the length-squared L-function, to identify clustering patterns of network-constrained flows. We first use the L-function and its derivative to examine the clustering scales. Further, we calculate the local L-function to ascertain the locations of the clustering patterns. In synthetic and practical experiments, our method can identify flow clustering patterns of high intensities and reveal the residents' main travel behavior trends with taxi OD flows, providing more reasonable suggestions for urban planning. |
| WOS关键词 | K-FUNCTION ; SPATIAL-PATTERNS ; DOMAIN |
| 资助项目 | The authors would also like to thank anonymous reviewers for their valuable comments on the manuscript. |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001087416700001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | The authors would also like to thank anonymous reviewers for their valuable comments on the manuscript. |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/199087]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Pei, Tao |
| 作者单位 | 1.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Peoples R China 2.Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou, Peoples R China 3.Nanjing Univ, Sch geog & Ocean Sci, Nanjing, Peoples R China 4.Hubei Univ, Sch Comp Sci & Informat Engn, Wuhan, Peoples R China 5.Univ Chinese Acad Sci, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fang, Zidong,Shu, Hua,Song, Ci,et al. Length-squared L-function for identifying clustering pattern of network-constrained flows[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH,2023,16(2):4191-4211. |
| APA | Fang, Zidong.,Shu, Hua.,Song, Ci.,Chen, Jie.,Liu, Xiaohan.,...&Pei, Tao.(2023).Length-squared L-function for identifying clustering pattern of network-constrained flows.INTERNATIONAL JOURNAL OF DIGITAL EARTH,16(2),4191-4211. |
| MLA | Fang, Zidong,et al."Length-squared L-function for identifying clustering pattern of network-constrained flows".INTERNATIONAL JOURNAL OF DIGITAL EARTH 16.2(2023):4191-4211. |
入库方式： OAI收割
来源：地理科学与资源研究所
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