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A study evaluating the Prithvi-EO-2.0 foundation model for satellite-based flood mapping across 19 diverse global flood events, finding that detection accuracy is jointly governed by land cover and flood type.
This paper introduces a novel uncertainty-aware PINN framework for flood inference from SAR data, addressing 'physics shock' by dynamically relaxing physical constraints in noisy regions. Evaluated on Sen1Floods11, the method achieves a 25% improvement in IoU and provides calibrated uncertainty bounds for operational disaster response.