A physics-aware meta-learning framework retrieves coastal biogeochemical parameters from hyperspectral Rrs by pretraining a base model on synthetic data from a bio-optical forward model and fine-tuning on regional in situ samples, outperforming benchmarks with good temporal agreement.
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Region-adaptable retrieval of coastal biogeochemical parameters from near-surface hyperspectral remote sensing reflectance using physics-aware meta-learning
A physics-aware meta-learning framework retrieves coastal biogeochemical parameters from hyperspectral Rrs by pretraining a base model on synthetic data from a bio-optical forward model and fine-tuning on regional in situ samples, outperforming benchmarks with good temporal agreement.