A CFSFDP clustering-based eddy trajectory tracking method

Wang Huizan; Guo Peng; Ni Qinbiao; Li Jiaxun

doi:10.3969/j.issn.0253-4193.2018.08.001

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Wang Huizan, Guo Peng, Ni Qinbiao, Li Jiaxun. A CFSFDP clustering-based eddy trajectory tracking method[J]. Haiyang Xuebao, 2018, 40(8): 1-9. doi: 10.3969/j.issn.0253-4193.2018.08.001

Citation:

Wang Huizan, Guo Peng, Ni Qinbiao, Li Jiaxun. A CFSFDP clustering-based eddy trajectory tracking method[J]. Haiyang Xuebao, 2018, 40(8): 1-9. doi: 10.3969/j.issn.0253-4193.2018.08.001

Wang Huizan, Guo Peng, Ni Qinbiao, Li Jiaxun. A CFSFDP clustering-based eddy trajectory tracking method[J]. Haiyang Xuebao, 2018, 40(8): 1-9. doi: 10.3969/j.issn.0253-4193.2018.08.001

Citation:

Wang Huizan, Guo Peng, Ni Qinbiao, Li Jiaxun. A CFSFDP clustering-based eddy trajectory tracking method[J]. Haiyang Xuebao, 2018, 40(8): 1-9. doi: 10.3969/j.issn.0253-4193.2018.08.001

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A CFSFDP clustering-based eddy trajectory tracking method

doi: 10.3969/j.issn.0253-4193.2018.08.001

1.
Institute of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China;State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
2.
Unit 94587, Lianyungang 222345, China
3.
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China;State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, China
4.
Naval Institute of Hydrographic Surveying and Charting, Tianjin 300061, China

Received Date: 2017-06-10
Rev Recd Date: 2017-10-30

Abstract

Abstract

Information extraction of ocean mesoscale eddies includes the eddy identification and its trajectory tracking, both of which are very important for the research on mesoscale eddies based on the massive data. The traditional methods of trajectory tracking generally need to be set the threshold of the search radius beforehand, which could introduce a certain degree of subjectivity. To improve the existing problem of the traditional methods, an automatic tracking method of the mesoscale eddies is proposed in this study based on the Clustering by Fast Search and Find of Density Peaks (CFSFDP) from clustering point of view. Then it was compared with the traditional similarity algorithm by taking the South China Sea as a testbed. Our results show that:(1) Based on the CFSFDP algorithm, the automatic tracking of mesoscale eddies is realized, and the accuracy is better than the traditional similarity method; (2) The proposed tracking algorithm is less dependent on the data integrity especially for the presence of partial missing data; (3) Our proposed tracking method has stronger adaptability, which overcomes the problem that the search radius need to be set beforehand in the traditional method.
- mesoscale eddies,
- trajectory tracking,
- Clustering by Fast search and Find of Density peaks(CFSFDP),
- South China Sea

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References(20)

References

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