Great Lakes ice classification using satellite C-band SAR multi-polarization data

The objective of this study is to advance development of algorithms to classify and map ice cover on the Laurentian Great Lakes using satellite C-band synthetic aperture radar (SAR) multi-polarization data. During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes ice types, using the Jet Propulsion Laboratory C-band scatterometer, were acquired together with surface-based ice physical characterization measurements and environmental parameters, concurrently with European Remote Sensing Satellite 2 (ERS-2) and RADARSAT-1 SAR data. This fully polarimetric dataset, composed of over 20 variations of different ice types measured at incidence angles from 0° to 60° for all polarizations, was processed and fully calibrated to obtain radar backscatter, establishing a library of signatures for different ice types. Computer analyses of calibrated ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using the library in a supervised classification technique indicate that different ice types in the ice cover can be identified and mapped, but that wind speed and direction can cause misclassification of open water as ice based on single frequency, single polarization data. Using RADARSAT-2 quad-pol and ENVISAT ASAR dual-pol data obtained for Lake Superior during the 2009 and 2011 winter seasons, algorithms were developed for small incidence angle (<35°) and large incidence angle (>35°) SAR images and applied to map ice and open water. Ice types were subsequently classified using the library of backscatter signatures. Ice-type maps provide important input for environmental management, ice-breaking operations, ice forecasting and modeling, and climate change studies.