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
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
  • Received Date: 2017-10-13
  • Rev Recd Date: 2017-12-22
  • Publish Date: 2018-10-27
  • 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.
  • [1] 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 and Lewis P E (eds.). Proceedings Volume 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VⅢ. Orlando, FL, United States:SPIE, 65-71. doi: 10.1117/12.478737
    [2] Chao J L, Liu C Y, Xu Y J et al., 2015. Multi-angular thermal infrared emission characteristics of Bohai Sea ice based on in situ measurements. Journal of Glaciology, 61(229):864-874. doi: 10.3189/2015JoG14J143
    [3] Feng Shizuo, Li Fengqi, Li Shaojing, 1999. An Introduction to Marine Science. Beijing:China Higher Education Press. (in Chinese)
    [4] Gu W, Liu C, Yuan S et al., 2013. Spatial distribution characteris-tics of sea-ice-hazard risk in Bohai, China. Annals of Glaciol-ogy, 54(62):73-79. doi: 10.3189/2013AoG62A303
    [5] Gu W, Lin Y, Xu Y et al., 2012. Sea ice desalination under the force of gravity in low temperature environments. Desalination, 295:11-15. doi: 10.1016/j.desal.2012.03.017
    [6] 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, 23(2):10-14, 18. (in Chinese)
    [7] Ji Shunying, Yue Qianjin, 2011. Engineering Sea Ice-The Nu-merical Model and Its Application. Beijing:Science Press. (in Chinese)
    [8] Li Zhijun, Lu Peng, Sodhi D S, 2004. Ice engineering sub-areas in Bohai from ice physical and mechanical parameters. Advances in Water Science, 15(5):598-602. (in Chinese)
    [9] Liu C Y, Chao J L, Gu W et al., 2015. 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. doi: 10.1080/15481603.2015.1007777
    [10] Liu Chengyu, Gu Wei, Li Lantao et al., 2013. Sea ice monitoring for the Bohai Sea based on the Hyperion image. Marine Science Bulletin, 32(2):200-207. (in Chinese)
    [11] 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
    [12] 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
    [13] 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.
    [14] Maykut G A, 1986. The surface heat and mass balance. In:Unter-steiner N (ed.). The Geophysics of Sea Ice. Boston:Springer, 395-464.
    [15] 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
    [16] 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.
    [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
    [18] Wu Kuiqiao, Xu Ying, Hao Yimeng, 2005. Application in sea ice remote sensing of MODIS data. Marine Forecasts, 22(S):44-49. (in Chinese)
    [19] 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)
    [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
    [21] 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)
    [22] Yang Guojin. 2000. Sea Ice Engineering. Beijing:China Petroleum Industry Press, 1-90, 455-480. (in Chinese)
    [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
    [46]  
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Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

doi: 10.1007/s11769-018-0986-y
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)
    Corresponding author: LIU Chengyu. E-mail:chengyuliu@vip.qq.com

Abstract: 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.

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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