Cyanobacteria blooms are recurrent in the Baltic Sea with frequency and intensity increasing with temperature. By relying on autonomous multispectral measurements from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), this study exploited an unprecedented dataset of in situ remote sensing reflectance RRS(λ) spectra (with wavelength λ in the interval 400–667 nm) acquired during filamentous cyanobacteria blooms in the Baltic Sea. The study investigated the temporal evolution of the in situ RRS(λ) during these blooms with particular emphases on those spectral features that may show potential to identify cyanobacteria and their development stages. Additionally, it assessed operational satellite Ocean Colour RRS(λ) products from the Ocean and Land Colour Instrument (OLCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) in the presence of cyanobacteria, for which only qualitative evaluations are available from previous studies. To ascertain to what extent satellite operational data products could be used for cyanobacteria detection in the Baltic Sea, the comparison of in situ and satellite derived RRS(λ) showed poor agreement with differences particularly pronounced at the blue centre-wavelengths. Nevertheless, band-differences in the green-red spectral region for OLCI and for MODIS exhibited less dependence on atmospheric correction issues with mean absolute relative differences between 8.3% and 9.6% for OLCI and between 12.6% and 12.9% for MODIS in the presence of cyanobacteria. Additionally, they showed potential to indicate the presence and development stage of cyanobacteria blooms in Baltic Sea waters while not being sensitive to other algal blooms.

Cazzaniga, I., Zibordi, G., Melin, F. (2023). Spectral features of ocean colour radiometric products in the presence of cyanobacteria blooms in the Baltic Sea. REMOTE SENSING OF ENVIRONMENT, 287 [10.1016/j.rse.2023.113464].

Spectral features of ocean colour radiometric products in the presence of cyanobacteria blooms in the Baltic Sea

Cazzaniga I.
;
2023

Abstract

Cyanobacteria blooms are recurrent in the Baltic Sea with frequency and intensity increasing with temperature. By relying on autonomous multispectral measurements from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), this study exploited an unprecedented dataset of in situ remote sensing reflectance RRS(λ) spectra (with wavelength λ in the interval 400–667 nm) acquired during filamentous cyanobacteria blooms in the Baltic Sea. The study investigated the temporal evolution of the in situ RRS(λ) during these blooms with particular emphases on those spectral features that may show potential to identify cyanobacteria and their development stages. Additionally, it assessed operational satellite Ocean Colour RRS(λ) products from the Ocean and Land Colour Instrument (OLCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) in the presence of cyanobacteria, for which only qualitative evaluations are available from previous studies. To ascertain to what extent satellite operational data products could be used for cyanobacteria detection in the Baltic Sea, the comparison of in situ and satellite derived RRS(λ) showed poor agreement with differences particularly pronounced at the blue centre-wavelengths. Nevertheless, band-differences in the green-red spectral region for OLCI and for MODIS exhibited less dependence on atmospheric correction issues with mean absolute relative differences between 8.3% and 9.6% for OLCI and between 12.6% and 12.9% for MODIS in the presence of cyanobacteria. Additionally, they showed potential to indicate the presence and development stage of cyanobacteria blooms in Baltic Sea waters while not being sensitive to other algal blooms.
Articolo in rivista - Articolo scientifico
Baltic Sea; Cyanobacteria; Harmful algal blooms; Ocean colour; Remote sensing reflectance;
English
6-feb-2023
2023
287
113464
open
Cazzaniga, I., Zibordi, G., Melin, F. (2023). Spectral features of ocean colour radiometric products in the presence of cyanobacteria blooms in the Baltic Sea. REMOTE SENSING OF ENVIRONMENT, 287 [10.1016/j.rse.2023.113464].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/504644
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