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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, Vol. 21, No. 5, pp. 235-248

Application of wavelet analysis to identify long-term patterns of blooming in Voronezh Reservoir using Landsat satellite images

A.A. Eliseev 1 , К.Yu. Silkin 1 
1 Voronezh State University, Voronezh, Russia
Accepted: 10.09.2024
DOI: 10.21046/2070-7401-2024-21-5-235-248
An irregular set of multispectral Landsat satellite imagery data allowed us to analyze the spatiotemporal patterns of water blooms in Voronezh Reservoir. This reservoir is entirely located within the administrative boundaries of a million-plus city and its harmful condition seriously reduces the living comfort of the population. In addition, the waters of Voronezh Reservoir are indirectly used for drinking water supply, which is fraught with serious problems for the social sphere of the city. Remote sensing is traditionally used to monitor the condition of such objects. We have proposed an improved formulation of the transform of multispectral data — the normalized difference algae index (NDAI), which allows us to objectively assess the intensity of phytoplankton reproduction in a given reservoir. Like all similar indexes, NDAI is a convenient tool for an informed solution to the type of problems for which it was created and some others. We have developed and applied a system for monitoring NDAI values taking into account the morphological features of this water body, which is a river-bed reservoir in the form of an extended bending channel. We obtained a typical seasonal variation of NDAI values for the reservoir over almost 40 years of observations. The period when Voronezh Reservoir usually “blooms” the most is recorded — the end of August or the beginning of September. We performed a wavelet analysis of a long-term series of NDAI values (minus the seasonal trend) to identify its inherent periodic components. We found that 2- and 12-year cycles predominate. We also analyzed the identified patterns and attempted a short-term forecast of the state of Voronezh Reservoir due to its bloom.
Keywords: Landsat, water bloom, Voronezh Reservoir, NDAI, algoindex, wavelet analysis, natural cyclicity, forecast
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References:

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