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.
Using lidar and snotel data for evaluating the performance of snow water equivalent retrieval using sentinel-1 repeat-pass interferometry
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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.