Spatiotemporal Variability of Cyanobacteria Blooms from Their MODIS-Based Automatic Identification

• Published in: Izvestiya. Atmospheric and oceanic physics 2022-12, Vol.58 (9), p.981-992
• Main Authors: Lishaev, P. N., Aleskerova, A. A., Kubryakov, A. A., Vasilenko, N. V., Stanichny, S. V.
• Format: Article
• Language: English
• Subjects: Algorithms; Blooms; Climatology; Cyanobacteria; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; Interannual variability; Landsat; Landsat satellites; MODIS; Remote sensing; Rivers; Satellite data; Use of Space Information about the Earth Studying Seas and Oceans from Space; Variability; Wind speed
• ISSN: 0001-4338; 1555-628X
• DOI: 10.1134/S0001433822090134

An automatic algorithm is proposed for identifying areas of cyanobacteria (CB) blooms in the Azov Sea based on an analysis of the optical spectra of MODIS satellite data. The algorithm has been validated by comparison with high-resolution quasi-synchronous Landsat data. The results obtained with this algorithm were used to study the spatiotemporal variability of CB blooms in the Azov Sea in 2003–2019 and give examples of the evolution of blooms in individual years. CB blooms in the Azov Sea are observed from March to November with a peak in August. The most intense and longest CB blooms are observed in Taganrog Bay. In the spring months, they spread from here eastward along the northern coast. In June–July, CB begin to intensively spread southward along the eastern coast and then, in some years, they penetrate into the center of the basin under the action of anticyclonic currents. An analysis of interannual variability has shown that the intensity of blooms was the highest in 2004–2011, with a peak in 2008–2009, and dropped significantly in 2011–2019. One reason for this drop is the decreased flow of the Don and Kuban rivers, as well as the increased wind speed observed in recent years.