Title :
A Polarimetric Decomposition Method for Ice in the Bohai Sea Using C-Band PolSAR Data
Author :
Xi Zhang ; Dierking, Wolfgang ; Jie Zhang ; Junmin Meng
Author_Institution :
First Inst. of Oceanogr., State Oceanic Adm., Qingdao, China
Abstract :
In recent years, there has been an increased interest in using synthetic aperture radar (SAR) to detect and monitor sea ice in the Bohai Sea for protecting offshore exploration and supporting marine transport. Two important tasks are the classification of sea ice and the determination of sea ice thickness, which can be achieved by considering the specific scattering mechanisms of the different ice types. This paper describes a three-component scattering model to decompose polarimetric SAR (PolSAR) data of sea ice. The total backscatter is modeled as the incoherent summation of surface, double-bounce, volume, and residual components. The proposed model extends the volume scattering contribution of sea ice by considering transmission, extinction, and refraction effects. The model is validated using C-band Radarsat-2 quad-polarization data acquired over sea ice in the Bohai Sea. The results show that the proposed polarimetric decomposition approach helps to distinguish different ice types and offers a proxy for sea ice thickness.
Keywords :
geophysical image processing; image classification; oceanographic regions; oceanographic techniques; radar polarimetry; remote sensing by radar; sea ice; synthetic aperture radar; Bohai Sea; C-band PolSAR data; C-band Radarsat-2 quad-polarization data; extinction effects; polarimetric decomposition method; refraction effects; sea ice classification; sea ice thickness; synthetic aperture radar; three-component scattering model; total backscatter model; transmission effects; volume scattering contribution; Covariance matrices; Scattering; Sea ice; Sea surface; Solid modeling; Synthetic aperture radar; Polarimetric radar; scattering; sea ice; synthetic aperture radar (SAR);
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2014.2356552