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Spatiotemporal Modeling and Implementation for Radar-Based Rainfall Estimation
Kuang, Qiuming1; Yang, Xuebing1; Zhang, Wensheng1; Zhang, Guoping2
Source PublicationIEEE GEOSCIENCE AND REMOTE SENSING LETTERS
2016-08-01
Volume13Issue:11Pages:1601-1605
SubtypeArticle
AbstractRadar-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.
KeywordRadar Reflectivity Rain Processes Rainfall Estimation Spatiotemporal Model
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
DOI10.1109/LGRS.2016.2597170
WOS KeywordQUANTITATIVE PRECIPITATION ESTIMATION ; ALGORITHM ; NETWORK
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61432008 ; 61532006 ; 61472423 ; 61305018)
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000386255600003
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13324
Collection精密感知与控制研究中心_人工智能与机器学习
Affiliation1.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
Recommended Citation
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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