Improving Sea Ice Characterization in Dry Ice Winter Conditions Using Polarimetric Parameters from C- and L-Band SAR Data
作者： Mohammed Dabboor , Benoit Montpetit , Stephen Howell , Christian Haas
DOI: 10.3390/RS9121270
关键词:
摘要: Sea ice monitoring and classification is one of the main applications Synthetic Aperture Radar (SAR) remote sensing. C-band SAR imagery regarded as an optimal choice for sea applications; however, other frequencies has not been extensively assessed. In this study, we evaluate potential fully polarimetric L-band classifying during dry winter conditions compared to SAR. Twelve parameters are derived using sets C- capabilities discrimination between First Year Ice (FYI) Old (OI), which considered be a mixture Second (SYI) Multiyear (MYI), investigated. Feature vectors effective extracted used classification. Results indicate that provides high accuracy (98.99%) FYI OI in comparison obtained (82.17% 81.85%), expected. However, was found classify only MYI floes OI, while merging both SYI into separate class. This comes contrary SAR, classifies SYI. indicates new discriminating from by combining conditions.
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