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Proceedings Paper

Automatic identification and tracking the Arctic sea ice based on sequential images of FY-3A satellite
Author(s): Ying Zhou; Cai-lan Gong; Yong Hu; Peng Meng; Wei-wei Ma
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Paper Abstract

This paper developed an automatic identification and tracking method based on the gray feature and geometric feature of the Arctic sea ice in the satellite images. Firstly, sea ice was recognized from the image based on the different spectral characteristic of sea ice, sea water and cloud. Secondly, by considering the gray distribution feature of individual floe, the individual floe identification was performed by combining the sub-region bimodal threshold segmentation with gradient differential technique. Finally, on the basis of geometric feature of the identified floes, the matching of same individual floes in pair images was implemented. Meanwhile, the motion vectors of the matched floes in the pair images were calculated. A series image of the Fram Strait region in June 2011, which was obtained by the Medium Resolution Spectral Imager onboard FENGYUN 3A satellite (FY-3A/MERSI), was used to compute the sea ice motion. The direction of the resulting sea ice motion vectors were found to match well with the average velocity from 1978 to 2003 and the dominant wind and ocean currents in the region.

Paper Details

Date Published: 30 August 2013
PDF: 10 pages
Proc. SPIE 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications, 89101N (30 August 2013); doi: 10.1117/12.2034650
Show Author Affiliations
Ying Zhou, Shanghai Institute of Technical Physics (China)
Univ. of Chinese Academy of Sciences (China)
Cai-lan Gong, Shanghai Institute of Technical Physics (China)
Yong Hu, Shanghai Institute of Technical Physics (China)
Peng Meng, Shanghai Institute of Technical Physics (China)
Wei-wei Ma, Shanghai Institute of Technical Physics (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 8910:
International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications
Lifu Zhang; Jianfeng Yang, Editor(s)

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