A Deep Learning Model Using Satellite Ocean Color and Hydrodynamic Model to Estimate Chlorophyll-<i>a</i> Concentration

A Deep Learning Model Using Satellite Ocean Color and Hydrodynamic Model to Estimate Chlorophyll-<i>a</i> Concentration

In this study, we used convolutional neural networks (CNNs)—which are well-known deep learning models suitable for image data processing—to estimate the temporal and spatial distribution of chlorophyll-<i>a</i> in a bay. The training data required the construction of a deep learning mode...

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Bibliographic Details
Main Authors: Daeyong Jin, Eojin Lee, Kyonghwan Kwon, Taeyun Kim
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
deep learning
convolutional neural network
chlorophyll-<i>a</i>
satellite
hydrodynamic model
Online Access:https://www.mdpi.com/2072-4292/13/10/2003

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