Publications des scientifiques de l'IRD

Dorffer C., Jourdin F., Nguyen T.T.N., Devillers Rodolphe, Mouillot D., Fablet R. (2025). Observation-only deep learning for gappy satellite-derived ocean color data using 4DVarNet. IEEE Transactions on Geoscience and Remote Sensing, 63, 4212512 [12 p.]. ISSN 0196-2892.

Titre du document
Observation-only deep learning for gappy satellite-derived ocean color data using 4DVarNet
Année de publication
2025
Type de document
Article référencé dans le Web of Science WOS:001626459000022
Auteurs
Dorffer C., Jourdin F., Nguyen T.T.N., Devillers Rodolphe, Mouillot D., Fablet R.
Source
IEEE Transactions on Geoscience and Remote Sensing, 2025, 63, 4212512 [12 p.] ISSN 0196-2892
Monitoring optical properties of coastal and open ocean waters is crucial to assessing the health of marine ecosystems. Deep learning offers a promising approach to address these ecosystem dynamics, especially in scenarios where gapfree ground-truth data is lacking, which poses a challenge for designing effective training frameworks. Using an advanced neural variational data assimilation scheme (called 4DVarNet), we introduce a comprehensive training framework designed to effectively train directly on gappy data sets. Using the Mediterranean Sea as a case study, our experiments not only highlight the high performance of the chosen neural network in reconstructing gap-free images from gappy datasets but also demonstrate its superior performance over state-of-the-art algorithms such as DInEOF and end-to-end neural mapping schemes based CNN or UNet architectures.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Limnologie / Océanographie : généralités [030] ; Informatique [122] ; Télédétection [126]
Localisation
Fonds IRD [F B010095766]
Identifiant IRD
fdi:010095766
Contact