Sea ice classification using dual polarization SAR data

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Huiying, Liu^1,2 ; Huadong, Guo^1 ; Lu, Zhang^1

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China^1

University of Chinese Academy of Sciences, Beijing, China^2

关键词: Angular dependence;    Backscattering coefficients;    Classification results;    Dual-polarization SAR;    Gray level co occurrence matrix(GLCM);    Sea ice classification;    Sea ice concentration;    Texture features;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012115/pdf
DOI  :  10.1088/1755-1315/17/1/012115

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Sea ice is an indicator of climate change and also a threat to the navigation security of ships. Polarimetric SAR images are useful in the sea ice detection and classification. In this paper, backscattering coefficients and texture features derived from dual polarization SAR images are used for sea ice classification. Firstly, the HH image is recalculated based on the angular dependences of sea ice types. Then the effective gray level co-occurrence matrix (GLCM) texture features are selected for the support vector machine (SVM) classification. In the end, because sea ice concentration can provide a better separation of pancake ice from old ice, it is used to improve the SVM result. This method provides a good classification result, compared with the sea ice chart from CIS.