Enhanced scan statistic with tightened window for detecting irregularly shaped hotspots
文献类型：期刊论文
| 作者 | Yan, Xiaorui4; Fu, Zhuoting4; Pei, Tao3,4; Song, Ci4; Fang, Zidong4; Liu, Xiaohan4; Gao, Meng2; Chen, Xiao4; Chen, Jie |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2024-09-04 |
| 卷号 | N/A |
| 关键词 | Hotspot detection spatial scan statistics tightened window irregular shape taxi pick-up point data |
| DOI | 10.1080/13658816.2024.2399144 |
| 产权排序 | 1 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | In spatial point data, a hotspot is defined as a group of points with a significantly higher density within an arbitrarily shaped area. Among existing hotspot identification methods, spatial scan statistic, known for its simple mechanism in locating hotspots, has been extensively studied and applied in various fields. However, existing methods rely on pre-defined scanning window shapes, e.g. generic geometries like circles or pre-divided regions, like administrative divisions, and thereby may not accurately capture the irregular shapes of hotspots. This study enhances the spatial scan statistic by introducing a tightened window, which is defined as the window tightened to align with the hotspot's shape. In our method, without the necessity of outlining the exact geometry, the area of the tightened window, estimated using the nearest distance statistics, is used for calculating the objective function. Experiments with simulated data demonstrate that our method outperforms existing methods in terms of testing hotspots' significance, identifying arbitrarily shaped hotspots, estimating hotspots' spatial extent, and reducing subjectivity in parameter selection. An empirical study using taxi pick-up point data shows our method can identify regions with high taxi demand and potential traffic congestion, including subway exits and commercial streets. |
| WOS关键词 | KERNEL DENSITY-ESTIMATION ; NEAREST-NEIGHBOR METHOD ; CLUSTERING-ALGORITHM ; SPATIAL ASSOCIATION ; DBSCAN |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| WOS记录号 | WOS:001306201700001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/207985]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Pei, Tao |
| 作者单位 | 1.Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.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 | Yan, Xiaorui,Fu, Zhuoting,Pei, Tao,et al. Enhanced scan statistic with tightened window for detecting irregularly shaped hotspots[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2024,N/A. |
| APA | Yan, Xiaorui.,Fu, Zhuoting.,Pei, Tao.,Song, Ci.,Fang, Zidong.,...&Chen, Jie.(2024).Enhanced scan statistic with tightened window for detecting irregularly shaped hotspots.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,N/A. |
| MLA | Yan, Xiaorui,et al."Enhanced scan statistic with tightened window for detecting irregularly shaped hotspots".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE N/A(2024). |
入库方式： OAI收割
来源：地理科学与资源研究所
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