Deep learning model achieves 0.81 correlation with lidar snow depth from Sentinel-1 InSAR, outperforming physics-based retrievals at 0.47 correlation, with demonstrated temporal and spatial transferability.
The airborne snow observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo
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Deep Learning-Based Snow Depth Retrieval Using Sentinel-1 Repeat-Pass InSAR
Deep learning model achieves 0.81 correlation with lidar snow depth from Sentinel-1 InSAR, outperforming physics-based retrievals at 0.47 correlation, with demonstrated temporal and spatial transferability.