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Estimation of the particulate organic carbon to chlorophyll-a ratio using modis-aqua in the East/Japan sea, South Korea

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Abstract
In recent years, the change of marine environment due to climate change and declining primary productivity have been big concerns in the East/Japan Sea, Korea. However, the main causes for the recent changes are still not revealed clearly. The particulate organic carbon (POC) to chlorophyll-a (chl-a) ratio (POC:chl-a) could be a useful indicator for ecological and physiological conditions of phytoplankton communities and thus help us to understand the recent reduction of primary productivity in the East/Japan Sea. To derive the POC in the East/Japan Sea from a satellite dataset, the new regional POC algorithm was empirically derived with in-situ measured POC concentrations. A strong positive linear relationship (R2 = 0.6579) was observed between the estimated and in-situ measured POC concentrations. Our new POC algorithm proved a better performance in the East/Japan Sea compared to the previous one for the global ocean. Based on the new algorithm, long-term POC:chl-a ratios were obtained in the entire East/Japan Sea from 2003 to 2018. The POC:chl-a showed a strong seasonal variability in the East/Japan Sea. The spring and fall blooms of phytoplankton mainly driven by the growth of large diatoms seem to be a major factor for the seasonal variability in the POC:chl-a. Our new regional POC algorithm modified for the East/Japan Sea could potentially contribute to long-term monitoring for the climate-associated ecosystem changes in the East/Japan Sea. Although the new regional POC algorithm shows a good correspondence with in-situ observed POC concentrations, the algorithm should be further improved with continuous field surveys. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Author(s)
Lee D.Son S.Joo H.Kim K.Kim M.J.Jang H.K.Yun M.S.Kang, Chang-KeunLee S.H.
Issued Date
2020-03
Type
Article
DOI
10.3390/rs12050840
URI
https://scholar.gist.ac.kr/handle/local/12282
Publisher
MDPI AG
Citation
Remote Sensing, v.12, no.5, pp.2720
ISSN
2072-4292
Appears in Collections:
Department of Environment and Energy Engineering > 1. Journal Articles
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