Chlorophyll-a Prediction Based on Machine Learning and Satellite Data in the South Sea of Korea

Chlorophyll-a (Chl-a) is a critical indicator of phytoplankton biomass, offering key insights into changes in marine ecosystems, including algal blooms and nutrient cycling. However, predicting Chl-a concentrations using numerical models remains challenging due to the intricate interplay of climatic...

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Bibliographic Details
Main Authors: Heejun Kim, Bong-Guk Kim, Kuk Jin Kim, Tae-Ho Kim, Hye-Kyeong Shin, Jin Hyun Han
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/11086093/
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