Knowledge Commons of Institute of Automation,CAS
Spatiotemporal Modeling and Implementation for Radar-Based Rainfall Estimation | |
Kuang, Qiuming1; Yang, Xuebing1; Zhang, Wensheng1; Zhang, Guoping2 | |
发表期刊 | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS |
2016-08-01 | |
卷号 | 13期号:11页码:1601-1605 |
文章类型 | Article |
摘要 | Radar-based rainfall estimation is one of the most important inputs for various meteorological applications. Although exciting progresses have been made in this area, accurate real-time rainfall estimation is still a significant opening topic that requires practical modeling. The research study presented in this letter improves rainfall estimation accuracy by proposing a random forest and linear chain conditional random-field-based spatiotemporal model (RANLIST). To apply this model for rainfall estimation, the implementing approach is presented. The advantages are listed as follows: 1) RANLIST improves rainfall estimation accuracy by exploiting both underlying local spatial structure of multiple radar reflectivity factors and time-series information of rain processes. 2) The time-series information of rain processes can be utilized in virtue of the presented implementation method. Experiments have been carried out over the radar-covered area of Quanzhou, China, in June and July 2014. Results show that RANLIST is superior to previous works. |
关键词 | Radar Reflectivity Rain Processes Rainfall Estimation Spatiotemporal Model |
WOS标题词 | Science & Technology ; Physical Sciences ; Technology |
DOI | 10.1109/LGRS.2016.2597170 |
关键词[WOS] | QUANTITATIVE PRECIPITATION ESTIMATION ; ALGORITHM ; NETWORK |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(61432008 ; 61532006 ; 61472423 ; 61305018) |
WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS类目 | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS记录号 | WOS:000386255600003 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/13324 |
专题 | 多模态人工智能系统全国重点实验室_人工智能与机器学习(杨雪冰)-技术团队 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China 2.China Meteorol Adm, Publ Meteorol Serv Ctr, Beijing 100081, Peoples R China |
第一作者单位 | 精密感知与控制研究中心 |
推荐引用方式 GB/T 7714 | Kuang, Qiuming,Yang, Xuebing,Zhang, Wensheng,et al. Spatiotemporal Modeling and Implementation for Radar-Based Rainfall Estimation[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2016,13(11):1601-1605. |
APA | Kuang, Qiuming,Yang, Xuebing,Zhang, Wensheng,&Zhang, Guoping.(2016).Spatiotemporal Modeling and Implementation for Radar-Based Rainfall Estimation.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,13(11),1601-1605. |
MLA | Kuang, Qiuming,et al."Spatiotemporal Modeling and Implementation for Radar-Based Rainfall Estimation".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 13.11(2016):1601-1605. |
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