| 基于SAR图像纹理的北极海冰厚度的反演研究 |
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| 引用本文： | 于淼,卢鹏,李志军,石立坚.基于SAR图像纹理的北极海冰厚度的反演研究[J].极地研究,2018,30(3):329-337. |
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| 作者姓名： | 于淼 卢鹏 李志军 石立坚 |
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| 作者单位： | 1. 大连理工大学海岸和近海工程国家重点实验室, 辽宁 大连 116024;
2. 国家卫星海洋应用中心, 北京 100081;3.国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081 |
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| 基金项目： | 国家重点研发计划专项(2016YFC1402702)、国家自然科学基金面上项目(41676187, 41376186)、国家国际科技合作专项(2011DFA22260)资助 |
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| 摘 要： | 基于七景北极Radarsat-2 SAR图像以及中国第六次北极科学考察走航期间利用船侧录像观测获得的平整冰厚度数据,通过灰度共生矩阵计算纹理,确定了最适合反演海冰厚度的纹理参数。并分析了海冰厚度与纹理之间的相关关系,探讨了纹理反演海冰厚度的可能性。选取了最合适的纹理特征进行拟合,并利用所得经验方程进行反演验证,结果与实测数据吻合较好,平均相对误差13.7%。与传统的仅依靠后向散射系数反演海冰厚度进行对比,新方法的误差更小,证明了纹理特征反演冰厚的优势。
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| 关 键 词： | 北极 海冰厚度 灰度共生矩阵 纹理 |
| 收稿时间： | 2017-08-30 |
Arctic sea ice thickness retrieval based on SAR image texture feature |
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| Yu Miao,Lu Peng,Li Zhijun,Shi Lijian.Arctic sea ice thickness retrieval based on SAR image texture feature[J].Chinese Journal of Polar Research,2018,30(3):329-337. |
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| Authors: | Yu Miao Lu Peng Li Zhijun Shi Lijian |
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| Abstract: | Utilize 7 Arctic SAR images and level ice thickness from 6th Arctic Survey，calculate texture feature through gray level co-occurrence matrix(GLCM)，confirm suitable GLCM parameters for thickness retrieval，analyze the relationship between sea-ice thickness and texture feature，validate the possibility of sea-ice thickness retrieval from texture feature. Then confirm fitting equation depending on the most suitable texture feature. When validated，the sea-ice thickness retrieval from the empirical equation agrees well with the in-situ data，the average relative error is 13.7%. This value is smaller compared with the commonly used method that only depend on backscattering coefficient，confirm the role of texture feature in sea-ice thickness retrieval. |
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| Keywords: | Arctic sea-ice thickness gray level co-occurrence matrix(GLCM) texture feature |
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