YUAN Shuai, GU Wei, LIU Chengyu, XIE Feng. Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea[J]. Acta Oceanologica Sinica, 2017, 36(1): 80-89. doi: 10.1007/s13131-017-0996-0
Citation: YUAN Shuai, GU Wei, LIU Chengyu, XIE Feng. Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea[J]. Acta Oceanologica Sinica, 2017, 36(1): 80-89. doi: 10.1007/s13131-017-0996-0

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

doi: 10.1007/s13131-017-0996-0
  • Received Date: 2016-01-05
  • Rev Recd Date: 2016-07-08
  • 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 semi-empirical 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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  • 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
    Beck R. 2003. EO-1 User Guide v. 2.3. Ohio:University of Cincinnati
    Feng Shizuo, Li Fengqi, Li Shaojing. 1999. An Introduction to Marine Science (in Chinese). Beijing:China Higher Education Press, 463
    Grenfell T C. 1983. A theoretical model of the optical properties of sea ice in the visible and near infrared. Journal of Geophysical Re-search, 88(C14):9723-9735
    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
    Gu Wei, Liu Chengyu, Yuan Shuai, et al. 2013. Spatial distribution characteristics of seaice-hazard risk in Bohai, China. Annals of Glaciology, 54(62):73-79
    Guo Qiaozhen, Gu Wei, Li Jing, et al. 2008. Research on the seaice disaster risk in Bohai Sea based on the remote sensing. Journal of Catastrophology (in Chinese), 23(2):10-14, 18
    Ji Shunying, Yue Qianjin. 2011. Engineering Sea Ice-The Numerical Model and Its Application (in Chinese). Beijing:Science Press
    Kauufman L, Rousseeuw P J. 2009. Finding Groups in Data:An Intro-duction to Cluster analysis. New York:John Wiley & Sons
    Lee Z, Carder K L, Mobley C D, et al. 1999. Hyperspectral remote sensing for shallow waters:2. Deriving bottom depths and wa-ter properties by optimization. Applied Optics, 38(18):3831-3843
    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
    Li Zhijun, Lu Peng, Sodhi D S. 2004. Ice engineering sub-areas in Bo-hai from ice physical and mechanical parameters. Advances in Water Science (in Chinese), 15(5):598-602
    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
    Liu Chengyu, Chao Jinlong, Gu Wei, et al. 2014a. On the surface roughness characteristics of the land fast seaice in the Bohai Sea. Acta Oceanologica Sinica, 33(7):97-106
    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
    Liu Meijie, Dai Yongshou, Zhang Jie, et al. 2015b. PCA-based seaice image fusion of optical data by HIS transform and SAR data by wavelet transform. Acta Oceanologica Sinica, 34(3):59-67
    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
    Liu Chengyu, Shao Honglan, Xie Feng, et al. 2014b. Sea ice density es-timation in the Bohai Sea using the hyperspectral remote sens-ing technology. In:Larar A M, Suzuki M, Wang Jianyu, eds. Pro-ceedings of SPIE 9263, Multispectral, Hyperspectral, and Ul-traspectral Remote Sensing Technology, Techniques and Ap-plications 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
    Mobley C D. 1995. Hydrolight 3.0 User's Guide. Menlo Park:SRI In-ternational
    Ning Li, Xie Feng, Gu, Wei, et al. 2009. Using remote sensing to estim-ate sea ice thickness in the Bohai Sea, China based on ice type. International Journal of Remote Sensing, 30(17):4539-4552
    Pearlman J S, Barry P S, Segal C C, et al. 2003. Hyperion, a space-based imaging spectrometer. IEEE Transactions on Geoscience and Remote Sensing, 41(6):1160-1173
    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 Sym-posium. New Jersey:Institute of Electrical and Electronics En-gineers, 4864-4867
    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
    Tong Qingxi, Zhang Bing, Zheng Lanfen. 2006. Hyperspectral Re-mote Sensing (in Chinese). Beijing:China Higher Education Press
    Warren S G. 1984. Optical constants of ice from the ultraviolet to the microwave. Applied Optics, 23(8):1206-1225
    Wu Kuiqiao, Xu Ying, Hao Yimeng. 2005. Application in sea ice remote sensing of MODIS data. Maritime Forecasts (in Chinese), 22(S):44-49
    Wu Longtao, Wu Huiding, Sun Lantao, et al. 2006. Retrieval of sea ice in the Bohai Sea from MODIS data. Periodical of Ocean Uni-versity of China (in Chinese), 36(2):173-179
    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
    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
    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
    Yang Guojin. 2000. Sea Ice Engineering (in Chinese). Beijing:China Petroleum Industry Press, 1-90, 455-480
    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
    Zege E P, Malinka A V, Katsev I L, et al. 2013. New approach for radi-ative transfer in sea ice and its application for sea ice satellite remote sensing. AIP Conference Proceedings, 1531(1):43-46
    Zhang Xi. 2011. Research of sea ice thickness detection by polarimet-ric SAR in Bohai Sea (in Chinese)[dissertation]. Qingdao:Ocean University of China
    Zhang Xi, Dierking W, Zhang Jie, et al. 2015. A polarimetric decom-position 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
    Zhang Xi, Zhang Jie, Meng Junmin, et al. 2013. Analysis of multi-di-mensional SAR for determining the thickness of thin ice sea ice in the Bohai Sea. Chinese Journal of Oceanology and Limno-logy, 31(3):681-698
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