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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Prediction Method for Large Diatom Appearance with Meteorological Data and MODIS Derived Turbidity and Chlorophyll-A in Ariake Bay Area in Japan

Author 1: Kohei Arai

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080306

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 3, 2017.

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Abstract: Prediction method for large diatom appearance in winter with meteorological data and MODIS derived turbidity and chlorophyll-a in Ariake Bay Area in Japan is proposed. Mechanism for large diatom appearance in winter is discussed with the influencing factors, meteorological condition and in-situ data of turbidity, chlorophyll-a data with the measuring instruments equipped at the Saga University own Tower in the Ariake Bay area. Particularly, the method for estimation of turbidity is still under discussion. Therefore, the algorithm for estimation of turbidity with MODIS data is proposed here. Through experiments, it is found that the proposed prediction method for large diatom appearance is validated with the meteorological data and MODIS derived turbidity as well as chlorophyll-a data estimated for the winter (from January to March) in 2012 and 2015.

Keywords: chlorophyl-a concentration; red tide; diatom; MODIS; satellite remote sensing

Kohei Arai, “Prediction Method for Large Diatom Appearance with Meteorological Data and MODIS Derived Turbidity and Chlorophyll-A in Ariake Bay Area in Japan” International Journal of Advanced Computer Science and Applications(IJACSA), 8(3), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080306

@article{Arai2017,
title = {Prediction Method for Large Diatom Appearance with Meteorological Data and MODIS Derived Turbidity and Chlorophyll-A in Ariake Bay Area in Japan},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080306},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080306},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {3},
author = {Kohei Arai}
}


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