Data-Driven Reconstruction of Sea Surface Turbidity Dynamics with 4dVarNet Neural Scheme Applied To Gappy Satellite Images-Reference-Cited by-同舟云学术

Data-Driven Reconstruction of Sea Surface Turbidity Dynamics with 4dVarNet Neural Scheme Applied To Gappy Satellite Images

Published:2023-07-16 Issue: Volume: Page:
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Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Dorffer C.¹,Jourdin F.²,Mouillot D.³,Devillers R.⁴,Fablet R.¹,Febvre Quentin¹

Affiliation:

1. IMT-Atlantique,UMR CNRS Lab-STICC, INRIA Team Odyssey,Brest,France

2. Service Hydrographique et Océanographique de la Marine (Shom),Brest,France

3. University of Montpellier, CNRS, IFREMER, IRD,MARBEC,Montpellier,France

4. Station SEAS-OI,Espace-Dev (IRD-UM-UG-UR-UA-UNC),Saint-Pierre,La Réunion,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281712.pdf?arnumber=10281712

Reference10 articles.

1. 4dvarnet-ssh: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry;beauchamp;Geoscientific Model Development Discussions,2022

2. Gap-Filling and Missing Information Recovery for Time Series of MODIS Data Using Deep Learning-Based Methods

3. End-to-End Neural Interpolation of Satellite-Derived Sea Surface Suspended Sediment Concentrations

4. CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

5. Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature

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