Researchers at Zhejiang University Target Machine Learning (Retrieving the Conce ntration of Particulate Inorganic Carbon for Cloud-covered Coccolithophore Bloom Waters Based On a Machine-learning Approach)
Researchers at Zhejiang University Target Machine Learning (Retrieving the Conce ntration of Particulate Inorganic Carbon for Cloud-covered Coccolithophore Bloom Waters Based On a Machine-learning Approach)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting from Zhoushan, People’s Republic o f China, by NewsRx journalists, research stated, “Coccolithophores are one of th e dominant algae in Arctic oceans and play an essential role in the carbon cycle given that they are the primary source of ocean particulate inorganic carbon (P IC). Ocean color remote sensing provides a powerful tool to observe the variatio n in coccolithophore blooms; however, heavy cloud cover prohibits satellite obse rvation coverage and frequency in Arctic oceans, which causes uncertainties in c haracterizing the phenological features of coccolithophore blooms.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from Zhejiang Univers ity, “In this study, a machine-learning-based empirical approach was developed t o extend the quantity of existing standard PIC products from ocean color satelli te observations for coccolithophore bloom waters under cloud cover conditions. R esults showed that the machine-learning-based approach successfully recovered th e PIC product from cloud cover conditions and filled the data gap generated by t he default PIC algorithm. The new approach profoundly increased the frequency an d coverage of ocean color satellite observations of PIC during coccolithophore b looms and provided detailed information in characterizing the phenology features of coccolithophore blooms.”
Key words
Zhoushan/People’s Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/Zhejiang University
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