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Assessment of C-band compact polarimetry SAR for sea ice classification

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Abstract

The C-band synthetic aperture radar (SAR) data from the Bohai Sea of China, the Labrador Sea in the Arctic and the Weddell Sea in the Antarctic are used to analyze and discuss the sea ice full polarimetric information reconstruction ability under compact polarimetric modes. The type of compact polarimetric mode which has the highest reconstructed accuracy is analyzed, along with the performance impact of the reconstructed pseudo quad-pol SAR data on the sea ice detection and sea ice classification. According to the assessment and analysis, it is recommended to adopt the CTLR mode for reconstructing the polarimetric parameters σ 0HH , σ 0VV , H and α, while for reconstructing the polarimetric parameters σ 0HV , ρ H-V, λ 1 and λ 2, it is recommended to use the π/4 mode. Moreover, it is recommended to use the π/4 mode in studying the action effects between the electromagnetic waves and sea ice, but it is recommended to use the CTLR mode for studying the sea ice classification.

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References

  • Boularbah S, Ouarzeddine M, Belhadj-Aissa A. 2012. Investigation of the capability of the compact polarimetry mode to Reconstruct Full Polarimetry mode using RADARSAT-2 data. Advanced Electromagnetics, 1(1): 19–28

    Article  Google Scholar 

  • Charbonneau F J, Brisco B, Raney R K, et al. 2010. Compact polarimetry overview and applications assessment. Canadian Journal of Remote Sensing: Journal Canadien de Télédétection, 36(S2): S298–S315

    Article  Google Scholar 

  • Cloude S R, Pottier E. 1997. An entropy based classification scheme for land applications of polarimetric SAR. IEEE Transactions on Geoscience and Remote Sensing, 35(1): 68–78

    Article  Google Scholar 

  • Collins M J, Denbina M, Atteia G. 2013. On the reconstruction of quad-pol SAR data from compact polarimetry data for ocean target detection. IEEE Transactions on Geoscience and Remote Sensing, 51(1): 591–600

    Article  Google Scholar 

  • Dabboor M, Geldsetzer T. 2014. Towards sea ice classification using simulated RADARSAT Constellation Mission compact polarimetric SAR imagery. Remote Sensing of Environment, 140: 189–195

    Article  Google Scholar 

  • Dabboor M, Howell S, Shokr M, et al. 2014. The Jeffries–Matusita distance for the case of complex Wishart distribution as a separability criterion for fully polarimetric SAR data. International Journal of Remote Sensing, 35(19): 6859–6873

    Google Scholar 

  • Dierking W, Skriver H, Gudmandsen P. 2003. SAR polarimetry for sea ice classification. In: Lacoste H, ed. Proceedings of the Workshop on POLinSAR-Applications of SAR Polarimetry and Polarimetric Interferometry (ESA SP-529). Frascati, Italy: CDROM, 18–22

    Google Scholar 

  • Geldsetzer T, Yackel J J. 2009. Sea ice type and open water discrimination using dual co-polarized C-band SAR. Canadian Journal of Remote Sensing, 35(1): 73–84

    Article  Google Scholar 

  • Gu Wei, Liu Chengyu, Yua Shuai, et al. 2013. Spatial distribution characteristics of sea-ice-hazard risk in Bohai, China. Annals of Glaciology, 54(62): 73–79

    Article  Google Scholar 

  • Guo Hao, Fan Qing, Zhang Xi, et al. 2014. Multifeature fusion for polarimetric synthetic aperture radar image classification of sea ice. Journal of Applied Remote Sensing, 8(1): 083534

    Article  Google Scholar 

  • Huynen J R. 1970. Phenomenological theory of radar targets [dissertation]. Rotterdam, NW: Drukkerij Bronder-Offset

    Google Scholar 

  • Jardon F P, Vivier F, Vancoppenolle M, et al. 2013. Full-depth desalination of warm sea ice. Journal of Geophysical Research: Oceans, 118(1): 435–447

    Google Scholar 

  • Lee J S, Grunes M R, Ainsworth T L, et al. 1999. Unsupervised classification using polarimetric decomposition and the complex Wishart classifier. IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2249–2258

    Article  Google Scholar 

  • Lee J S, Pottier E. 2009. Polarimetric radar imaging: from basics to applications. Boca: CRC Press

    Book  Google Scholar 

  • Nghiem S V, Kwok R, Yueh S H, et al. 1995. Polarimetric signatures of sea ice: 2. Experimental observations. Journal of Geophysical Research: Oceans, 100(C7): 13681–13698

    Article  Google Scholar 

  • Nord M E, Ainsworth T L, Lee J S, et al. 2009. Comparison of compact polarimetric synthetic aperture radar modes. IEEE Transactions on Geoscience and Remote Sensing, 47(1): 174–188

    Article  Google Scholar 

  • Ochilov S, Clausi D A. 2012. Operational SAR sea-ice image classification. IEEE Transactions on Geoscience and Remote Sensing, 50(11): 4397–4408

    Article  Google Scholar 

  • Prinsenberg S J, Peterson I K, Holladay J S, et al. 2012. Labrador shelf pack ice and iceberg survey, March 2011: Canadian technical report of hydrography and ocean sciences. v 275. Goose Bay, Labrador: Canadian Helicopters Ltd, 1–44

    Google Scholar 

  • Raney R K. 2007. Hybrid-polarity SAR architecture. IEEE Transactions on Geoscience and Remote Sensing, 45(11): 3397–3404

    Article  Google Scholar 

  • Salberg A B, Rudjord O, Solberg A H S. 2014. Oil spill detection in hybrid- polarimetric SAR images. IEEE Transactions on Geoscience and Remote Sensing, 52(10): 6521–6533

    Article  Google Scholar 

  • Scheuchl B, Cumming I, Hajnsek I. 2005. Classification of fully polarimetric single- and dual-frequency SAR data of sea ice using the Wishart statistics. Canadian Journal of Remote Sensing, 31(1): 61–72

    Article  Google Scholar 

  • Souyris J C, Imbo P, Fjortoft R, et al. 2005. Compact polarimetry based on symmetry properties of geophysical media: The p/4 mode. IEEE Transactions on Geoscience and Remote Sensing, 43(3): 634–646

    Article  Google Scholar 

  • Stacy N, Preiss M. 2006. Compact polarimetric analysis of X-band SAR data. In: Proceedings of EUSAR 2006. Dresden, Germany: EUSAR

    Google Scholar 

  • Wakabayashi H, Matsuoka T, Nakamura K, et al. 2004. Polarimetric characteristics of sea ice in the Sea of Okhotsk observed by airborne L-band SAR. IEEE Transactions on Geoscience and Remote Sensing, 42(11): 2412–2425

    Article  Google Scholar 

  • Yang Guojin. 2000. Sea Ice Engineering Science (in Chinese). Beijing: Petroleum Industry Press

    Google Scholar 

  • Yin J J, Yang J, Zhou Z S. 2013. New parameters in compact polarimetry for ocean target detection. In: Proceedings of IET International Radar Conference 2013. Xi'an: IEEE, 1–6

    Google Scholar 

  • Zhang Xi, Dierking W, Zhang Jie, et al. 2015. A polarimetric decomposition method for ice in the Bohai Sea using C-band PolSAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(1): 47–66

    Article  Google Scholar 

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Correspondence to Meijie Liu.

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Foundaition item: The National Science Foundation for Young Scientists of China under contract No. 41306193; the National Special Research Fund for Non-profit Marine Sector under contract No. 201305025-2; the Dragon 3 Cooperation Programme under contract No. 10501 by the Ministry of Science and Technology of the P.R. China and the European Space Agency.

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Zhang, X., Zhang, J., Liu, M. et al. Assessment of C-band compact polarimetry SAR for sea ice classification. Acta Oceanol. Sin. 35, 79–88 (2016). https://doi.org/10.1007/s13131-016-0856-3

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  • DOI: https://doi.org/10.1007/s13131-016-0856-3

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