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Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters. / Кузьмина, Софья Константиновна; Лобанова, Полина Вячеславовна.

Complex Investigation of the World Ocean (CIWO-2023) : Proceedings of the VII International Conference of Young Scientists. Springer Nature, 2023. p. 456-462 (Springer Proceedings in Earth and Environmental Sciences (SPEES)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Кузьмина, СК & Лобанова, ПВ 2023, Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters. in Complex Investigation of the World Ocean (CIWO-2023) : Proceedings of the VII International Conference of Young Scientists. Springer Proceedings in Earth and Environmental Sciences (SPEES), Springer Nature, pp. 456-462, Complex Investigation of the World Ocean (CIWO-2023) VII International Conference of Young Scientists, Санкт-Петербург, Russian Federation, 15/05/23. https://doi.org/10.1007/978-3-031-47851-2_55

APA

Кузьмина, С. К., & Лобанова, П. В. (2023). Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters. In Complex Investigation of the World Ocean (CIWO-2023) : Proceedings of the VII International Conference of Young Scientists (pp. 456-462). (Springer Proceedings in Earth and Environmental Sciences (SPEES)). Springer Nature. https://doi.org/10.1007/978-3-031-47851-2_55

Vancouver

Кузьмина СК, Лобанова ПВ. Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters. In Complex Investigation of the World Ocean (CIWO-2023) : Proceedings of the VII International Conference of Young Scientists. Springer Nature. 2023. p. 456-462. (Springer Proceedings in Earth and Environmental Sciences (SPEES)). https://doi.org/10.1007/978-3-031-47851-2_55

Author

Кузьмина, Софья Константиновна ; Лобанова, Полина Вячеславовна. / Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters. Complex Investigation of the World Ocean (CIWO-2023) : Proceedings of the VII International Conference of Young Scientists. Springer Nature, 2023. pp. 456-462 (Springer Proceedings in Earth and Environmental Sciences (SPEES)).

BibTeX

@inproceedings{16158743734544e5a331fb3d32e3e49d,
title = "Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters",
abstract = "This study analyzes remotely sensed chlorophyll a (Chl a) concentration as an indicator of ocean productivity in the European Arctic Corridor (the Norwegian, Greenland, and Barents Seas), and its connection to physical environmental parameters: Photosynthetically Active Radiation (PAR), Sea Surface Temperature (SST), Mixed Layer Depth (MLD) and Sea Surface Salinity (SSS). Using the Random Forest Machine Learning algorithm in the Classifier modification we created models describing a correlation between Chl a and environmental parameters, and retrieved a total area of high-productivity zones (Chl a is more than 1 mg m−3) based on these correlations.This research was funded by the Saint Petersburg State University, project N 94033410.",
author = "Кузьмина, {Софья Константиновна} and Лобанова, {Полина Вячеславовна}",
year = "2023",
month = nov,
doi = "10.1007/978-3-031-47851-2_55",
language = "English",
isbn = "978-3-031-47850-5",
series = "Springer Proceedings in Earth and Environmental Sciences (SPEES)",
publisher = "Springer Nature",
pages = "456--462",
booktitle = "Complex Investigation of the World Ocean (CIWO-2023)",
address = "Germany",
note = "Complex Investigation of the World Ocean (CIWO-2023) VII International Conference of Young Scientists ; Conference date: 15-05-2023 Through 19-05-2023",
url = "http://kimocon.ru/",

}

RIS

TY - GEN

T1 - Modeling Chlorophyll a Concentration for the European Arctic Corridor Based on Environmental Parameters

AU - Кузьмина, Софья Константиновна

AU - Лобанова, Полина Вячеславовна

N1 - Conference code: 7

PY - 2023/11

Y1 - 2023/11

N2 - This study analyzes remotely sensed chlorophyll a (Chl a) concentration as an indicator of ocean productivity in the European Arctic Corridor (the Norwegian, Greenland, and Barents Seas), and its connection to physical environmental parameters: Photosynthetically Active Radiation (PAR), Sea Surface Temperature (SST), Mixed Layer Depth (MLD) and Sea Surface Salinity (SSS). Using the Random Forest Machine Learning algorithm in the Classifier modification we created models describing a correlation between Chl a and environmental parameters, and retrieved a total area of high-productivity zones (Chl a is more than 1 mg m−3) based on these correlations.This research was funded by the Saint Petersburg State University, project N 94033410.

AB - This study analyzes remotely sensed chlorophyll a (Chl a) concentration as an indicator of ocean productivity in the European Arctic Corridor (the Norwegian, Greenland, and Barents Seas), and its connection to physical environmental parameters: Photosynthetically Active Radiation (PAR), Sea Surface Temperature (SST), Mixed Layer Depth (MLD) and Sea Surface Salinity (SSS). Using the Random Forest Machine Learning algorithm in the Classifier modification we created models describing a correlation between Chl a and environmental parameters, and retrieved a total area of high-productivity zones (Chl a is more than 1 mg m−3) based on these correlations.This research was funded by the Saint Petersburg State University, project N 94033410.

UR - https://link.springer.com/book/10.1007/978-3-031-47851-2

UR - https://www.mendeley.com/catalogue/4ff58abd-911b-3e5e-ac82-76d8f73a7182/

U2 - 10.1007/978-3-031-47851-2_55

DO - 10.1007/978-3-031-47851-2_55

M3 - Conference contribution

SN - 978-3-031-47850-5

T3 - Springer Proceedings in Earth and Environmental Sciences (SPEES)

SP - 456

EP - 462

BT - Complex Investigation of the World Ocean (CIWO-2023)

PB - Springer Nature

T2 - Complex Investigation of the World Ocean (CIWO-2023) VII International Conference of Young Scientists

Y2 - 15 May 2023 through 19 May 2023

ER -

ID: 113571235