An auto-tracking algorithm for mesoscale eddies using global nearest neighbor filter

doi:10.1002/lom3.10156

	An auto-tracking algorithm for mesoscale eddies using global nearest neighbor filter
	Yi, Jiawei 1,2; Du, Yunyan 1,2; Liang, Fuyuan 3; Zhou, Chenghu 1,2
刊名	LIMNOLOGY AND OCEANOGRAPHY-METHODS
	2017-03-01
卷号	15 期号:3 页码:276-290
ISSN号	1541-5856
DOI	10.1002/lom3.10156
通讯作者	Du, Yunyan(duyy@lreis.ac.cn)
英文摘要	Many tracking algorithms have been developed to automatically track mesoscale ocean eddies. They are successful in most situations except when there is more than one successor candidate. This study presents a tracking approach using the global nearest neighbor filter (GNNF) to tackle this problem. The GNNF method implements the Kalman filter to model and track the process of ocean eddies, and then employs an optimization method to identify the most possible successor from the multiple candidates. The method was evaluated using an eddy dataset from the South China Sea (SCS) and its performance was compared against the distance-based search (DBS) and the overlap-based search (OBS) methods. Results show that GNNF is the most successful method to correctly identify a successor for a specific eddy with multiple potential candidates (accounts for nearly 2% of the total eddies in our dataset). We also evaluated the methods using synthetic eddy tracks and results show that the performance of all three methods is strongly affected by the number of tracks and the variations of eddy propagation velocity. The average pairing error of GNNF, DBS, and OBS are about 0.2%, 0.4%, and 0.5%, respectively, when the synthetic tracks were generated with experiment parameters best fit the survey results of ocean eddies in the SCS. The GNNF method is still the most successful algorithm in identifying the correct successor regardless of the complexity of synthetic tracks.
资助项目	National Science Foundation of China[41371378] ; National Science Foundation of China[41421001] ; China Scholarship Council
WOS关键词	SOUTH CHINA SEA ; EDDY DETECTION ; IDENTIFICATION ; VORTICES ; QUANTIFICATION ; CIRCULATION ; DYNAMICS ; GEOMETRY ; PERU
WOS研究方向	Marine & Freshwater Biology ; Oceanography
语种	英语
出版者	WILEY
WOS记录号	WOS:000397732400004
资助机构	National Science Foundation of China ; China Scholarship Council
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/64771]
专题	中国科学院地理科学与资源研究所
通讯作者	Du, Yunyan
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Western Illinois Univ, Dept Geog, Macomb, IL USA
推荐引用方式 GB/T 7714	Yi, Jiawei,Du, Yunyan,Liang, Fuyuan,et al. An auto-tracking algorithm for mesoscale eddies using global nearest neighbor filter[J]. LIMNOLOGY AND OCEANOGRAPHY-METHODS,2017,15(3):276-290.
APA	Yi, Jiawei,Du, Yunyan,Liang, Fuyuan,&Zhou, Chenghu.(2017).An auto-tracking algorithm for mesoscale eddies using global nearest neighbor filter.LIMNOLOGY AND OCEANOGRAPHY-METHODS,15(3),276-290.
MLA	Yi, Jiawei,et al."An auto-tracking algorithm for mesoscale eddies using global nearest neighbor filter".LIMNOLOGY AND OCEANOGRAPHY-METHODS 15.3(2017):276-290.