A multivariate spatial structure indicator based on geographic similarity
文献类型：期刊论文
| 作者 | Zhao, Fang-He4,5; Qin, Cheng-Zhi2,3,4,5; Zhu, A-Xing1; Pei, Tao4,5 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2025-02-08 |
| 卷号 | N/A |
| 关键词 | Spatial structure indicator designation multivariate dataset geographic similarity |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2025.2458639 |
| 产权排序 | 1 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Quantification of spatial structure reveals the distribution patterns of geographic features, which is essential for geographic analysis. For quantitative measurements of multivariate spatial structure, existing methods often neglect either the geographic meaning or the spatial combination of the multivariate dataset. In this paper, a new indicator for multivariate spatial structure (MuSS) is proposed. Since multivariate datasets characterize geographic conditions, the correlation between multivariate attributes at different locations can be measured as the similarity of geographic conditions. The MuSS indicator evaluates whether location pairs with closer distances have higher geographic similarities. Experimental results show that MuSS outperforms existing methods in differentiate multivariate datasets with varied spatial distribution patterns. A MuSS value deviating from 1 suggests that geographic similarity between location pairs is relevant to their distance, and the statistical significance of the captured distribution patterns is evaluated using a p-value from a permutation test. MuSS is also applied to real geographic data at different spatial resolutions in two study areas with diverse distribution patterns. Case studies show that MuSS provides consistent comparison results for spatial structure levels between study areas, while existing methods cannot. |
| URL标识 | 查看原文 |
| WOS关键词 | MORANS-I ; K-FUNCTION ; AUTOCORRELATION ; ASSOCIATION ; SAMPLE |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001417144900001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/212332]  |
| 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 | Zhu, A-Xing |
| 作者单位 | 1.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA 2.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Peoples R China; 3.Shaanxi Normal Univ, Sch Geog & Tourism, Xian, Peoples R China; 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China; 5.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhao, Fang-He,Qin, Cheng-Zhi,Zhu, A-Xing,et al. A multivariate spatial structure indicator based on geographic similarity[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2025,N/A. |
| APA | Zhao, Fang-He,Qin, Cheng-Zhi,Zhu, A-Xing,&Pei, Tao.(2025).A multivariate spatial structure indicator based on geographic similarity.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,N/A. |
| MLA | Zhao, Fang-He,et al."A multivariate spatial structure indicator based on geographic similarity".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE N/A(2025). |
入库方式： OAI收割
来源：地理科学与资源研究所
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