Sea ice can be difficult to study because of the remote and hazardous locations in which is exists. Remotely sensed SAR data is one half of the equation. To complete the analysis, SAR processing software with the right algorithms are required.
Polarimetric signatures of different ice types were analyzed at four radar incidence angles. The results were compared with previous studies to examine the variation of signatures with varying geophysical and SAR parameters. The study was further extended to investigate the potential of polarimetric parameters for ice type discrimination. This was done by analyzing the polarimetric signatures in one and twodimensional feature spaces and also through a combination of adopted classifi cation algorithms.
University of Calgary
In this study, developed by PhD candidates at the University of Calgary, the classifi cation potential of polarimetric parameters derived after Cloude–Pottier decomposition, Touzi decomposition, Freeman–Durden decomposition, normalized radar cross section measurements, phase differences, and statistical synthetic aperture radar correlation measures is evaluated by relating them to three pre-identifi ed sea ice types and wind-roughened open water.
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