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This paper builds upon the large-scale dataset pairing MetOp radiances with ERA5 PBLH labels, and presents the best-performing architecture found: a dual-encoder Transformer whose masked-input handling lets it operate in all weather conditions.
This work introduces GEOID-Flood, a large-scale multi-modal flood segmentation benchmark, derived from Copernicus Emergency Management Service activations, and reports three main findings: foundation models offer a consistent but modest advantage; optical-SAR fusion with finetuning best resolves transient flooding; and...
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