Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature

Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature

The forecasting and reconstruction of oceanic dynamics is a crucial challenge. While model driven strategies are still the state-of-the-art approaches in the reconstruction of spatio-temporal dynamics. The ever increasing availability of data collections in oceanography raised the relevance of data-...

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Bibliographic Details
Main Authors: Said Ouala, Ronan Fablet, Cédric Herzet, Bertrand Chapron, Ananda Pascual, Fabrice Collard, Lucile Gaultier
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Remote Sensing
Subjects:
data assimilation
dynamical model
Kalman filter
neural networks
data-driven models
interpolation
Online Access:https://www.mdpi.com/2072-4292/10/12/1864

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