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Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

YUAN Shuai LIU Chengyu LIU Xueqin

YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. 中国地理科学, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
引用本文: YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. 中国地理科学, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. Chinese Geographical Science, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
Citation: YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. Chinese Geographical Science, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y

Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

doi: 10.1007/s11769-018-0986-y
基金项目: Under the auspices of the National Natural Science Foundation of China (No. 41306091), Public Science and Technology Research Funds Projects of Ocean (No. 201505019-2)
详细信息
    通讯作者:

    LIU Chengyu. E-mail:chengyuliu@vip.qq.com

Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

Funds: Under the auspices of the National Natural Science Foundation of China (No. 41306091), Public Science and Technology Research Funds Projects of Ocean (No. 201505019-2)
More Information
    Corresponding author: LIU Chengyu. E-mail:chengyuliu@vip.qq.com
  • 摘要: Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this study, a practical model of sea ice thickness (PMSIT) was proposed based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In the proposed model, the MODIS data of the first band were used to estimate sea ice thickness and the difference between the second-band reflectance and the fifth-band reflectance in the MODIS data was calculated to obtain the difference attenuation index (DAI) of each pixel. The obtained DAI was used to estimate the integrated attenuation coefficient of the first band of the MODIS at the pixel level. Then the model was used to estimate sea ice thickness in the Bohai Sea with the MODIS data and then validated with the actual sea ice survey data. The validation results showed that the proposed model and corresponding parameterization scheme could largely avoid the estimation error of sea ice thickness caused by the spatial and temporal heterogeneity of sea ice extinction and allowed the error of 18.7% compared with the measured sea ice thickness.
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    [17] Su H, Wang Y P, 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. doi: 10.1029/2012JC008251
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    [20] Xie F, Gu W, Ha S 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. doi: 10.1080/01431160600589153
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    [23] Yuan S, Gu W, Liu C Y et al., 2017. Towards a semi-empirical model of sea ice thickness based on hyperspectral remote sensing in the Bohai Sea. Acta Oceanologica Sinica, 36(1):80-89. doi: 10.1007/s13131-017-0996-0
    [24] Yuan S, Gu W, Xu Y J et al., 2012. The estimate of sea ice re-sources quantity in the Bohai Sea based on NOAA/AVHRR data. Acta Oceanologica Sinica, 31(1):33-40. doi:10.1007/s 13131-012-0173-4
    [25] Zeng T, Shi L J, Marko M et al., 2016. Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery. Acta Oceanologica Sinica, 35(7):96-104. doi:10.1007/s 13131-016-0908-8
    [26] Zhang Xi, 2011. Research on Sea Ice Thickness Detection by Polarimetric SAR in Bohai Sea. Qingdao:Ocean University of China. (in Chinese)
    [27] Zhang X, Dierking W, Zhang J et al., 2015. A polarimetric de-composition 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. doi: 10.1109/JSTARS.2014.2356552
    [28] Zhang X, Zhang J, Meng J M et al., 2013. Analysis of mul-ti-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea. Chinese Journal of Oceanology and Limnology, 31(3):681-698. doi:10.1007/s00343-013-2057-7r> Liu M J, Dai Y S, Zhang J et al., 2015.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.doi:10.1007/s13131-015-0634-7
    [29] Liu W S, Sheng H, Zhang X, 2016.Sea ice thickness estimation in the Bohai Sea using geostationary ocean color imager data.Acta Oceanologica Sinica, 35(7):105-112.doi:10.1007/s 13131-016-0910-1
    [30] Luo Y W, Wu H D, Zhang Y F et al., 2004.Application of the HY-1 satellite to sea ice monitoring and forecasting.Acta Oceanologica Sinica, 23(3):251-266.
    [31] Maykut G A, 1986.The surface heat and mass balance.In:Unter-steiner N (ed.).The Geophysics of Sea Ice.Boston:Springer, 395-464.
    [32] Ning L, Xie F, Gu W et al., 2009.Using remote sensing to esti-mate sea ice thickness in the Bohai Sea, China based on ice type.International Journal of Remote Sensing, 30(17):4539-4552.doi: 10.1080/01431160802592542
    [33] Shi L J, Karvonen J, Cheng B et al., 2014.Sea ice thickness re-trieval from SAR imagery over Bohai sea.In:2014 IEEE In-ternational Geoscience and Remote Sensing Symposium.Quebec City, QC, Canada:Institute of Electrical and Electronics Engineers, 4864-4867.
    [34] Su H, Wang Y P, 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.doi: 10.1029/2012JC008251
    [35] Wu Kuiqiao, Xu Ying, Hao Yimeng, 2005.Application in sea ice remote sensing of MODIS data.Marine Forecasts, 22(S):44-49. (in Chinese)
    [36] 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, 36(2):173-179. (in Chinese)
    [37] Xie F, Gu W, Ha S 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.doi: 10.1080/01431160600589153
    [38] Xie Feng, Gu Wei, Yuan Yi et al., 2003.Estimation of sea ice resources in Liaodong gulf using remote sensing.Resources Science, 25(3):17-23. (in Chinese)
    [39] Yang Guojin.2000.Sea Ice Engineering.Beijing:China Petroleum Industry Press, 1-90, 455-480. (in Chinese)
    [40] Yuan S, Gu W, Liu C Y et al., 2017.Towards a semi-empirical model of sea ice thickness based on hyperspectral remote sensing in the Bohai Sea.Acta Oceanologica Sinica, 36(1):80-89.doi: 10.1007/s13131-017-0996-0
    [41] Yuan S, Gu W, Xu Y J et al., 2012.The estimate of sea ice re-sources quantity in the Bohai Sea based on NOAA/AVHRR data.Acta Oceanologica Sinica, 31(1):33-40.doi:10.1007/s 13131-012-0173-4
    [42] Zeng T, Shi L J, Marko M et al., 2016.Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery.Acta Oceanologica Sinica, 35(7):96-104.doi:10.1007/s 13131-016-0908-8
    [43] Zhang Xi, 2011.Research on Sea Ice Thickness Detection by Polarimetric SAR in Bohai Sea.Qingdao:Ocean University of China. (in Chinese)
    [44] Zhang X, Dierking W, Zhang J et al., 2015.A polarimetric de-composition 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.doi: 10.1109/JSTARS.2014.2356552
    [45] Zhang X, Zhang J, Meng J M et al., 2013.Analysis of mul-ti-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea.Chinese Journal of Oceanology and Limnology, 31(3):681-698.doi: 10.1007/s00343-013-2057-7
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Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

doi: 10.1007/s11769-018-0986-y
    基金项目:  Under the auspices of the National Natural Science Foundation of China (No. 41306091), Public Science and Technology Research Funds Projects of Ocean (No. 201505019-2)
    通讯作者: LIU Chengyu. E-mail:chengyuliu@vip.qq.com

摘要: Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this study, a practical model of sea ice thickness (PMSIT) was proposed based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In the proposed model, the MODIS data of the first band were used to estimate sea ice thickness and the difference between the second-band reflectance and the fifth-band reflectance in the MODIS data was calculated to obtain the difference attenuation index (DAI) of each pixel. The obtained DAI was used to estimate the integrated attenuation coefficient of the first band of the MODIS at the pixel level. Then the model was used to estimate sea ice thickness in the Bohai Sea with the MODIS data and then validated with the actual sea ice survey data. The validation results showed that the proposed model and corresponding parameterization scheme could largely avoid the estimation error of sea ice thickness caused by the spatial and temporal heterogeneity of sea ice extinction and allowed the error of 18.7% compared with the measured sea ice thickness.

English Abstract

YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. 中国地理科学, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
引用本文: YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. 中国地理科学, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. Chinese Geographical Science, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
Citation: YUAN Shuai, LIU Chengyu, LIU Xueqin. Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data[J]. Chinese Geographical Science, 2018, 28(5): 863-872. doi: 10.1007/s11769-018-0986-y
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