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Multi-Sensor Approach to Ice Type Classification, Ice Thickness Measurement, and Ice PAR Attenuation in the Great Lakes

Author(s): G. Leshkevich; S. V. Nghiem; D. K. Hall; R. Shuchman

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Abstract: Measurements of ice type, concentration, thickness, and transmittance are essential for modeling ice growth, wintertime primary productivity estimates, and Coast Guard ice breaking operations in the Great Lakes. This paper describes the use of optical, synthetic aperture radar (SAR), and scatterometer sensors to acquire such measurements from satellite and airborne platforms. Initial validation of a satellite SAR algorithm to classify Great Lakes ice types showed that ice types can be classified using a library of ice backscatter signatures, but that open water can be misclassified owing to the ambiguity in single polarization data due to variations in wind speed/direction over water. RADARSAT-2 Quad-pol SAR data were used to first create an ice/water mask for both small and large incidence angle data. However, distinguishing ice and water is problematic using RADARSAT-2 ScanSAR Wide data due to the wide range of incidence angles in the data. Using Moderate-Resolution Imaging Spectroradiometer (MODIS) thermal infrared data to distinguish ice and water by surface temperature can remediate the ambiguity. Ice and water can also be identified using dual polarized scatterometer data as well as ice freeze-up and break-up dates. Over open water in Lake Superior, RADARSAT-2 SAR revealed features corresponding to cloud streets in MODIS observations. To aid in estimating lake-wide photosynthetically active radiation (PAR) transmittance through ice, in situ measurements of PAR (400-700 nm) transmittance through major ice types can be used with the maps of ice type to estimate lake-wide transmittance. Until satellite algorithms are developed for ice thickness retrieval, an airborne ground penetrating radar (GPR) can be used to acquire transects of ice thickness. Test flights of a GPR on a helicopter over snow ice/lake ice produced acceptably accurate ice thickness. Autonomous drones, tested in March 2016 for real-time ice reconnaissance, may serve as a platform for GPR snow and ice thickness measurements.


Year: 2016

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