Cyanobacteria index as a tool for the satellite detection of cyanobacteria blooms in the Baltic Sea

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konik_marta_remote sens_2023.pdf (4.23 MB)

Date

2023

Authors

Konik, Marta
Bradtke, Katarzyna
Stoń-Egiert, Joanna
Soja-Woźniak, Monika
Śliwińska-Wilczewska, Sylwia
Darecki, Miroslaw

Journal Title

Journal ISSN

Volume Title

Publisher

Remote Sensing

Abstract

Cyanobacteria blooms in the Baltic Sea have been studied for years due to their toxicity, which negatively affects all biota, along with the influence of these floating colonies on surface fluxes. However, mapping these blooms is still a challenge since their high dynamics, wide coverage, and specific radiometric footprint hinder atmospheric correction and negatively affect the quality of satellite images. In this study, we assessed the use of an alternative approach called the cyanobacteria index (CI), which is based on the reflectance spectral shape and which does not require comprehensive atmospheric correction. We demonstrated a close relationship between the positive CI values, indicating the presence of blooms, and the concentration of phycocyanin, the marker pigment of filamentous cyanobacteria in the Baltic Sea. We proved that the CI index could efficiently identify cyanobacteria-dominated blooms where colonies floated near the surface. Therefore, this index represents a valuable complement to the previous monitoring methods, suitable for extreme bloom events. The analysis of a time series of satellite images obtained between 2002 and 2018 using the CI index revealed the elongation of the bloom season, which may have been a consequence of the water temperature remaining within the cyanobacteria’s tolerance range for a longer time.

Description

Keywords

cyanobacteria index, remote sensing, OLCI, cyanobacteria blooms, HABs, Baltic Sea

Citation

Konik, M., Bradtke, K., Stoń-Egiert, J., Soja-Woźniak, M., Śliwińska-Wilczewska, S., & Darecki, M. (2023). Cyanobacteria index as a tool for the satellite detection of cyanobacteria blooms in the Baltic Sea. Remote Sensing, 15(6), 1601. https://doi.org/10.3390/rs15061601

URI

https://doi.org/10.3390/rs15061601
 http://hdl.handle.net/1828/15919

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We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.