The Cryospheric Science Group of the Interdisciplinary Centre on Climate Change (IC3) is pleased to welcome MSc candidate Garry Pan, to present his research at our seminar this month. His presentation is entitled:
"RADARSAT-2 Polarimetric Radar Imaging for Lake Ice Mapping"
Garry Pan1 and Claude R. Duguay1
University of Waterloo1
Changes in lake ice dates and duration are useful indicators for assessing long-term climate trends and variability in northern countries. Lake ice cover observations are also a valuable data source for predictions with numerical ice and weather forecasting models. In recent years, satellite remote sensing has assumed a greater role in providing observations of lake ice cover extent for both modeling and climate monitoring purposes. Polarimetric radar imaging has become a promising tool for lake ice mapping at high latitudes where meteorological conditions and polar darkness severely limit observations from optical sensors. In this study, we assessed and characterized the physical scattering mechanisms of lake ice from fully polarimetric RADARSAT-2 datasets obtained over Great Bear Lake, Canada, with the intent of classifying open water and different ice types during the freeze-up and break-up periods. Model-based and eigen-based decompositions were employed to construct the coherency matrix into deterministic scattering mechanisms. These procedures as well as basic polarimetric parameters were integrated into modified convolutional neural networks (CNN). The CNN was modified via introduction of a Markov random field into the higher iterative layers of networks for acquiring updated priors and classifying ice and open water areas over the lake. We show that the selected polarimetric parameters can help with interpretation of radar-ice/water interactions and can be used successfully for water-ice segmentation, including different ice types. As more satellite SAR sensors are being launched or planned, such as the Sentinel-1a/b series and the upcoming RADARSAT Constellation Mission, the rapid volume growth of data and their analysis require the development of robust automated algorithms. The approach developed in this study was therefore designed with the intent of moving towards fully automated mapping of lake ice for consideration by ice services.
Location Information
200 University Avenue West
2022
Waterloo , ON, CA N2L 3G1