Identification of Co-Clusters with Coherent Trends in Geo-Referenced Time Series
文献类型：期刊论文
| 作者 | Wu, Xiaojing |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2022-02-01 |
| 卷号 | 11期号:2页码:14 |
| 关键词 | co-clustering coherent trends The Netherlands temperature series data mining |
| DOI | 10.3390/ijgi11020134 |
| 通讯作者 | Wu, Xiaojing(wuxj@igsnrr.ac.cn) |
| 英文摘要 | Several studies have worked on co-clustering analysis of spatio-temporal data. However, most of them search for co-clusters with similar values and are unable to identify co-clusters with coherent trends, defined as exhibiting similar tendencies in the attributes. In this study, we present the Bregman co-clustering algorithm with minimum sum-squared residue (BCC_MSSR), which uses the residue to quantify coherent trends and enables the identification of co-clusters with coherent trends in geo-referenced time series. Dutch monthly temperatures over 20 years at 28 stations were used as the case study dataset. Station-clusters, month-clusters, and co-clusters in the BCC_MSSR results were showed and compared with co-clusters of similar values. A total of 112 co-clusters with different temperature variations were identified in the Results, and 16 representative co-clusters were illustrated, and seven types of coherent temperature trends were summarized: (1) increasing; (2) decreasing; (3) first increasing and then decreasing; (4) first decreasing and then increasing; (5) first increasing, then decreasing, and finally increasing; (6) first decreasing, then increasing, and finally decreasing; and (7) first decreasing, then increasing, decreasing, and finally increasing. Comparisons with co-clusters of similar values show that BCC_MSSR explored coherent spatio-temporal patterns in regions and certain time periods. However, the selection of the suitable co-clustering methods depends on the objective of specific tasks. |
| WOS关键词 | TEMPERATURE VARIABILITY ; PATTERNS |
| 资助项目 | National Natural Science Foundation of China[41901317] |
| WOS研究方向 | Computer Science ; Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000778178800001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/173260]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wu, Xiaojing |
| 作者单位 | Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Xiaojing. Identification of Co-Clusters with Coherent Trends in Geo-Referenced Time Series[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2022,11(2):14. |
| APA | Wu, Xiaojing.(2022).Identification of Co-Clusters with Coherent Trends in Geo-Referenced Time Series.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,11(2),14. |
| MLA | Wu, Xiaojing."Identification of Co-Clusters with Coherent Trends in Geo-Referenced Time Series".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 11.2(2022):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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