Application of assimilation and filtration methods for satellite water sensing data for plankton population evolution processes predictive modeling
https://doi.org/10.23947/2587-8999-2020-1-1-1-11
Abstract
The article is devoted to the analysis and implementation of satellite observations data assimilation and filtration highly technological methods used in the hydrodynamics and biological kinetics of shallow reservoirs mathematical models development and verification. The paper considers the using neural networks possibility and describes various methods for filtering images obtained from satellite earth sensing data. The plankton populations evolution mathematical model in the Azov sea is considered. Its calibration and verification is carried out using observations satellite assimilation methods. The purpose of this work is to create a software tool used at the preliminary and final stages of hydrobiological processes in shallow water mathematical modeling.
Keywords
mathematical modeling,
phytoplankton evolution,
shallow water reservoir,
satellite sensing data,
neural net-works,
filtering methods
Supporting agencies: The reported study was funded by RFBR, project № 19-31-51017.
About the Authors
A. L. Leontyev
Southern Federal University; Supercomputers and Neurocomputers Research Center; Scientific and Technological University «Sirius»
Russian Federation
Russian Federation
Anton L. Leontyev, Postgraduate student of the Department of Intelligent and multiprocessor systems
Chekhov st., 2, Taganrog
(918)510 29 20
A. V. Nikitina
Southern Federal University; Supercomputers and Neurocomputers Research Center; Scientific and Technological University «Sirius»
Russian Federation
Russian Federation
Alla V. Nikitina, Dr.Sci., professor, Professor of the Department of Intelligent and multiprocessor systems
Chekhov st., 2, Taganrog
8(951)516 85 38
M. I. Chumak
Scientific and Technological University «Sirius»; Don State Technical University
Russian Federation
Russian Federation
Margaret I. Chumak, Master student of the Department of Mathematics and computer science
Gagarin sq., 1, Rostov-on-Don
8(908)182 03 69
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Review
For citations:
Leontyev A.L., Nikitina A.V., Chumak M.I. Application of assimilation and filtration methods for satellite water sensing data for plankton population evolution processes predictive modeling. Computational Mathematics and Information Technologies. 2020;4(1):1-11. https://doi.org/10.23947/2587-8999-2020-1-1-1-11
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