ISSN 1995-4301

ISSN 2618-8406

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2 issue of the journal in 2022

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Application of methods for processing and analysis of satellite images for the study of eutrophied reservoirs (review)

Т.I. Kutyavina, G.Ya. Kantor, Т.Ya. Аshikhmina, V.P. Savinykh
Section: Theoretical problems of ecology
The review discusses the existing approaches and algorithms used to assess the water quality of inland water bodies in various climatic zones, provides formulas for calculating the most commonly used spectral indices (Chl-a, MCI, NDVI, Turb). The possibilities of using data of remote sensing of the Earth from various sensors (Modis-Terra, Modis-Aqua, Landsat-5, Landsat 7, Landsat 8, Sentinel-2, Sentinel-3) to study the quality of water in inland waters are described. Many researchers note the great potential of the Sentinel-3 satellite for studying inland waters with complex optical conditions (high turbidity, color, colored dissolved organic matter (CDOM) and total suspended matter). It is shown that the optical properties of inland waters differ depending on the trophic status of the reservoir, on the season of the year, the physicochemical composition of water, the species composition of phytoplankton and other factors. Currently, both traditional methods and new, improved algorithms are used to monitor the state of water bodies with complex optical conditions. Various methods of atmospheric corrections and calibrated spectral indices are used, classifications of reservoirs by the presence of phytoplankton particles, suspended particles of organic and inorganic matter, and CDOM are developed. It was noted that the concentration of chlorophyll a and the turbidity of the water are the most important biophysical parameters used to assess the quality of water and determine the ecological status of inland waters.
Keywords: inland waters, eutrophication, trophic status of a reservoir, phytoplankton, turbidity, transparency, remote sensing of the Earth
Article published in number 2 for 2020
DOI: 10.25750/1995-4301-2020-2-014-025
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The journal was founded in 2007