MODEL-BASED INTERPRETATION OF ERS-1 SAR IMAGES OF ARCTIC SEA-ICE

Interpretation of Synthetic Aperture Radar (SAR) images of sea ice is complex because of the natural variability of sea ice and sensor-induc ed effects, such as speckle. Most of the research on SAR image interpr etation has focused on the winter months and algorithms were developed to classify sea ice successfully under cold conditions. However, inte rpretation of SAR images during the seasonal transitions has proved di fficult due to rapidly changing weather conditions. In this paper we a ddress the application of SAR during the transition from summer to the fall freeze-up. This period is important because it signals the start of significant new ice growth, which affects the air-ocean heat excha nge and injects brine into the upper layers of the ocean. We have inte rpreted SAR images of the sea ice in terms of the basic ice characteri stics by using shipborne radar measurements of sea ice during the free ze-up and models derived from these measurements. We have shown that t he model-based approach is effective in interpreting SAR images during this seasonal transition. This work also provides the physical mechan isms responsible for the large increase in backscatter observed at the end of the summer melt season.