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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Detalhes bibliográficos

Principais autores:	Heejun Kim, Bong-Guk Kim, Kuk Jin Kim, Tae-Ho Kim, Hye-Kyeong Shin, Jin Hyun Han
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
coleção:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Assuntos:	Chlorophyll-a ensemble feature ablation study machine learning (ML) satellite data South Sea of Korea
Acesso em linha:	https://ieeexplore.ieee.org/document/11086093/
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