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Earth Observation-Based Cyanobacterial Bloom Index Testing for Ecological Status Assessment in the Open, Coastal and Transitional Waters of the Baltic and Black Seas

Authors :
Diana Vaičiūtė
Yevhen Sokolov
Martynas Bučas
Toma Dabulevičienė
Olga Zotova
Source :
Remote Sensing, Vol 16, Iss 4, p 696 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The use of Earth Observation (EO) for water quality monitoring has substantially raised in the recent decade; however, harmonisation of EO-based indicators across the seas to support environmental policies is in great demand. EO-based Cyanobacterial Bloom Index (CyaBI) originally developed for open waters, was tested for transitional and coastal waters of the Lithuanian Baltic Sea and the Ukrainian Black Sea during 2006–2019. Among three tested neural network-based processors (FUB-CSIRO, C2RCC, standard Level-2 data), the FUB-CSIRO applied to Sentinel-3 OLCI images was the most appropriate for the retrieval of chlorophyll-a in both seas (R2 = 0.81). Based on 147 combined MERIS and OLCI synoptic satellite images for the Baltic Sea and 234 for the Black Sea, it was shown that the CyaBI corresponds to the eutrophication patterns and trends over the open, coastal and transitional waters. In the Baltic Sea, the cyanobacteria blooms mostly originated from the central part and the outflow of the Curonian Lagoon. In the Black Sea, they occurred in the coastal region and shelf zone. The recent decrease in bloom presence and its severity were revealed in the areas with riverine influence and coastal waters. Intensive blooms significantly enhanced the short-term increase in sea surface temperature (mean ≤ 0.7 °C and max ≤ 7.0 °C) compared to surrounding waters, suggesting that EO data originating from thermal infrared sensors could also be integrated for the ecological status assessment.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.b657ec848f94c6a9d2e7234a644012d
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16040696