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Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea

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Abstract

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness (SEMSIT) that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands (spectral dimension information) are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.

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References

  • Anderson G P, Felde G W, Hoke M L, et al. 2002. MODTRAN4-based atmospheric correction algorithm: FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes). In: Shen S S, Lewis P E, eds. Proceedings of Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII. Bellingham: International Society for Optics and Photonics, 65–71

  • Austin R W, Halikas G. 1976. The Index of Refraction of Seawater. San Diego: University of California

    Google Scholar 

  • Beck R. 2003. EO-1 User Guide v. 2.3. Ohio: University of Cincinnati

    Google Scholar 

  • Feng Shizuo, Li Fengqi, Li Shaojing. 1999. An Introduction to Marine Science (in Chinese). Beijing: China Higher Education Press, 463

    Google Scholar 

  • Grenfell T C. 1983. A theoretical model of the optical properties of sea ice in the visible and near infrared. Journal of Geophysical Research, 88(C14): 9723–9735

    Article  Google Scholar 

  • Gu Wei, Lin Yebin, Xu Yingjun, et al. 2012. Sea ice desalination under the force of gravity in low temperature environments. Desalination, 295: 11–15

    Article  Google Scholar 

  • Gu Wei, Liu Chengyu, Yuan 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 Qiaozhen, Gu Wei, Li Jing, et al. 2008. Research on the sea-ice disaster risk in Bohai Sea based on the remote sensing. Journal of Catastrophology (in Chinese), 23(2): 10–14, 18

    Google Scholar 

  • Ji Shunying, Yue Qianjin. 2011. Engineering Sea Ice—The Numerical Model and Its Application (in Chinese). Beijing: Science Press

    Google Scholar 

  • Kauufman L, Rousseeuw P J. 2009. Finding Groups in Data: An Introduction to Cluster analysis. New York: John Wiley & Sons

    Google Scholar 

  • Lee Z, Carder K L, Mobley C D, et al. 1999. Hyperspectral remote sensing for shallow waters: 2. Deriving bottom depths and water properties by optimization. Applied Optics, 38(18): 3831–3843

    Article  Google Scholar 

  • Li Zhijun, Kong Xiangpeng, Zhang Yong, et al. 2009. Field investigations of piled ice forming in coastal area. Journal of Dalian Maritime University (in Chinese), 35(3): 9–12

    Google Scholar 

  • Li Zhijun, Lu Peng, Sodhi D S. 2004. Ice engineering sub-areas in Bohai from ice physical and mechanical parameters. Advances in Water Science (in Chinese), 15(5): 598–602

    Google Scholar 

  • Light B, Maykut G A, Grenfell T C. 2003. A two-dimensional Monte Carlo model of radiative transfer in sea ice. Journal of Geophysical Research, 108(C7): 3219

    Article  Google Scholar 

  • Liu Chengyu, Chao Jinlong, Gu Wei, et al. 2014a. On the surface roughness characteristics of the land fast sea-ice in the Bohai Sea. Acta Oceanologica Sinica, 33(7): 97–106

    Article  Google Scholar 

  • Liu Chengyu, Chao Jinlong, Gu Wei, et al. 2015a. Estimation of sea ice thickness in the Bohai Sea using a combination of VIS/NIR and SAR images. GIScience & Remote Sensing, 52(2): 115–130

    Article  Google Scholar 

  • Liu Meijie, Dai Yongshou, Zhang Jie, et al. 2015b. PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform. Acta Oceanologica Sinica, 34(3): 59–67

    Article  Google Scholar 

  • Liu Chengyu, Gu Wei, Li Lantao, et al. 2013. Sea ice monitoring for the Bohai Sea based on the Hyperion image. Marine Science Bulletin (in Chinese), 32(2): 200–207

    Google Scholar 

  • Liu Chengyu, Shao Honglan, Xie Feng, et al. 2014b. Sea ice density estimation in the Bohai Sea using the hyperspectral remote sensing technology. In: Larar A M, Suzuki M, Wang Jianyu, eds. Proceedings of SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V. Bellingham: International Society for Optics and Photonics, 92632T-1–8

  • Luo Yawei, Wu Huiding, Zhang Yunfei, et al. 2004. Application of the HY-1 satellite to sea ice monitoring and forecasting. Acta Oceanologica Sinica, 23(3): 251–266

    Google Scholar 

  • Mobley C D. 1995. Hydrolight 3.0 User's Guide. Menlo Park: SRI International

    Google Scholar 

  • Ning Li, Xie Feng, Gu Wei, et al. 2009. Using remote sensing to estimate sea ice thickness in the Bohai Sea, China based on ice type. International Journal of Remote Sensing, 30(17): 4539–4552

    Article  Google Scholar 

  • Pearlman J S, Barry P S, Segal C C, et al. 2003. Hyperion, a spacebased imaging spectrometer. IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1160–1173

    Article  Google Scholar 

  • Shi Lijian, Karvonen J, Cheng Bin, et al. 2014. Sea ice thickness retrieval from SAR imagery over Bohai sea. In: Proceedings of 2014 IEEE International Geoscience and Remote Sensing Symposium. New Jersey: Institute of Electrical and Electronics Engineers, 4864–4867

    Google Scholar 

  • Su Hua, Wang Yunpeng. 2012. Using MODIS data to estimate sea ice thickness in the Bohai Sea (China) in the 2009–2010 winter. Journal of Geophysical Research, 117(C10): C10018

    Article  Google Scholar 

  • Tong Qingxi, Zhang Bing, Zheng Lanfen. 2006. Hyperspectral Remote Sensing (in Chinese). Beijing: China Higher Education Press

    Google Scholar 

  • Warren S G. 1984. Optical constants of ice from the ultraviolet to the microwave. Applied Optics, 23(8): 1206–1225

    Article  Google Scholar 

  • Wu Kuiqiao, Xu Ying, Hao Yimeng. 2005. Application in sea ice remote sensing of MODIS data. Maritime Forecasts (in Chinese), 22(S): 44–49

    Google Scholar 

  • Wu Longtao, Wu Huiding, Sun Lantao, et al. 2006. Retrieval of sea ice in the Bohai Sea from MODIS data. Periodical of Ocean University of China (in Chinese), 36(2): 173–179

    Google Scholar 

  • Xie Simei, Bao Chenglan, Jiang Dezhong, et al. 2001. Role of sea ice in air-sea exchange and its relation to sea fog. Chinese Journal of Polar Science, 12(2): 119–132

    Google Scholar 

  • Xie Feng, Gu Wei, Ha Si, et al. 2006. An experimental study on the spectral characteristics of one year-old sea ice in the Bohai Sea, China. International Journal of Remote Sensing, 27(14): 3057–3063

    Article  Google Scholar 

  • Xie Feng, Gu Wei, Yuan Yi, et al. 2003. Estimation of sea ice thickness for sea ice resources in Liaodong Gulf using remote sensing. Resources Science (in Chinese), 25(3): 17–23

    Google Scholar 

  • Yang Guojin. 2000. Sea Ice Engineering (in Chinese). Beijing: China Petroleum Industry Press, 1–90, 455–480

    Google Scholar 

  • Yuan Shuai, Gu Wei, Xu Yingjun, et al. 2012. The estimate of sea ice resources quantity in the Bohai Sea based on NOAA/AVHRR data. Acta Oceanologica Sinica, 31(1): 33–40

    Article  Google Scholar 

  • Zege E P, Malinka A V, Katsev I L, et al. 2013. New approach for radiative transfer in sea ice and its application for sea ice satellite remote sensing. AIP Conference Proceedings, 1531(1): 43–46

    Article  Google Scholar 

  • Zhang Xi. 2011. Research of sea ice thickness detection by polarimetric SAR in Bohai Sea (in Chinese) [dissertation]. Qingdao: Ocean University of China

    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 

  • Zhang Xi, Zhang Jie, Meng Junmin, et al. 2013. Analysis of multi-dimensional SAR for determining the thickness of thin ice sea ice in the Bohai Sea. Chinese Journal of Oceanology and Limnology, 31(3): 681–698

    Article  Google Scholar 

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Authors and Affiliations

  1. National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian, 116023, China

    Shuai Yuan

  2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China

    Wei Gu

  3. Key Laboratory of Spatial Active Opto-electronic Techniques, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, 200083, China

    Chengyu Liu & Feng Xie

Authors
  1. Shuai Yuan
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  2. Wei Gu
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  3. Chengyu Liu
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  4. Feng Xie
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Corresponding author

Correspondence to Wei Gu.

Additional information

Foundation item: The National Natural Science Fundation of China under contract No. 41306091; the Public Science and Technology Research Funds Projects of Ocean under contract Nos 201105016 and 201505019.

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Yuan, S., Gu, W., Liu, C. et al. Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea. Acta Oceanol. Sin. 36, 80–89 (2017). https://doi.org/10.1007/s13131-017-0996-0

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  • DOI: https://doi.org/10.1007/s13131-017-0996-0

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