Multi-source deep data fusion and super-resolution for downscaling sea surface temperature guided by Generative Adversarial Network-based spatiotemporal dependency learning

Author:

Kim JinahORCID,Kim Taekyung,Ryu Joon-Gyu

Funder

Institute for Information and Communications Technology Promotion

Ministry of Science, ICT and Future Planning

National IT Industry Promotion Agency

Korea Institute of Ocean Science and Technology

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference51 articles.

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3. The accuracy of satellite-composite GHRSST and model-reanalysis sea surface temperature data at the seas adjacent to the Korean Peninsula;Baek;Ocean Polar Res.,2019

4. RAMSSA—An operational, high-resolution, regional Australian multi-sensor sea surface temperature analysis over the Australian region;Beggs;Aust. Meteorol. Oceanogr. J.,2011

5. Satellite sea surface temperature product comparison for the Southern African marine region;Carr;Remote Sens.,2021

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