Enhanced Reconstruction of Satellite-Derived Monthly Chlorophyll a Concentration With Fourier Transform Convolutional-LSTM-Reference-Cited by-同舟云学术

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Enhanced Reconstruction of Satellite-Derived Monthly Chlorophyll a Concentration With Fourier Transform Convolutional-LSTM

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Chen Siyu¹^ORCID,Deng Lin¹^ORCID,Zhao Jun¹^ORCID

Affiliation:

1. School of Marine Sciences, Sun Yat-sen University, Zhuhai, Guangdong, China

Funder

Southern Marine Science and Engineering Guangdong Laboratory

National Natural Science Foundation of China

Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10509652.pdf?arnumber=10509652

Reference34 articles.

1. Application of DINCAE to Reconstruct the Gaps in Chlorophyll-a Satellite Observations in the South China Sea and West Philippine Sea

2. A Bayesian approach for remote sensing of chlorophyll-a and associated retrieval uncertainty in oligotrophic and mesotrophic lakes

3. Deep learning in multimodal remote sensing data fusion: A comprehensive review

4. Inpainting of Remote Sensing SST Images With Deep Convolutional Generative Adversarial Network

5. An effective thin cloud removal procedure for visible remote sensing images

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