Algorithm of obtaining sea ice concentration using polarization features from fully polarimetric SAR data

doi:10.13474/j.cnki.11-2246.2024.0214

Abstract

Abstract: This paper proposes an algorithm to obtain sea ice concetration(SIC) from fully polarimetric SAR data based on polarization features. Firstly, multilookprocess and filtering are performed on the fully polarimetric SAR data to obtain the coherence matrix and covariance matrix. Secondly, a number of polarization features are obtained through the coherence matrix and covariance matrix, and the correlation and redundancy analysis of these polarization features is carried out to construct the optimal feature space.Then, put the optimal feature space as input into the neural network classifier to obtain the SIC result. Finally, extract the sea ice concentration according to the SIC result. In this paper, two fully polarimetric Radarsat-2 images in the southern waters of Labrador are used to obtain the SIC. Compared with the commercial the SIC product of ASI-3125, the algorithm results of this paper are basically consistent with the distribution trend of the SIC product of ASI-3125,and generally slightly larger than the SIC product of ASI-3125. The standard deviation distributions are 3.46% and 6.82%, indicating that the use of high-resolution fully polarimetric SAR data has advantages in monitoring small-sized broken sea ice in the marginal area.

Key words: Radarsat-2, sea ice, sea ice concentration, feature extraction, neural network

CLC Number:

P237

CHEN Xingzhe, XIE Tao, WANG Minghua, ZHANG Xuehong, LI Jian, BAI Shuying. Algorithm of obtaining sea ice concentration using polarization features from fully polarimetric SAR data[J]. Bulletin of Surveying and Mapping, 2024, 0(2): 80-84,89.

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