Detection of mucilage phenomenon in the Sea of Marmara by using multi-scale satellite data


Tuzcu Kokal A., Olğun Kıyak N., Musaoğlu N.

ENVIRONMENTAL MONITORING AND ASSESSMENT, vol.194, no.8, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 194 Issue: 8
  • Publication Date: 2022
  • Doi Number: 10.1007/s10661-022-10267-6
  • Journal Name: ENVIRONMENTAL MONITORING AND ASSESSMENT
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Compendex, EMBASE, Environment Index, Food Science & Technology Abstracts, Geobase, Greenfile, MEDLINE, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Marine mucilage, Remote sensing, Machine learning, The Sea of Marmara, Izmit Bay, TURKISH STRAITS SYSTEM, ADRIATIC SEA, PHYTOPLANKTON COMPOSITION, ENVIRONMENTAL-CONDITIONS, NOCTILUCA-SCINTILLANS, TEMPORAL VARIATIONS, EMILIANIA-HUXLEYI, DARDANELLES, DINOFLAGELLATE, EUTROPHICATION
  • Istanbul Technical University Affiliated: Yes

Abstract

Marine mucilage outbreaks occurred in the Sea of Marmara in 2021 which severely affected the marine ecosystem. The thick mucilage blankets with different colors became a public concern due to the toxicity potential related to pathogens that accumulate in prolonged presence of mucilage. The mucilage-covered areas in the Sea of Marmara detected by remote sensing data acquired in 2021 were previously reported. However, the areal extents and spectral characteristics of the different colored mucilage types remain unknown. This study presents the spectral characteristics of different types of mucilage in the Izmit Bay in the Sea of Marmara by using medium- (Sentinel-2) and high-spatial resolution (Worldview-3) satellite images. Also, the sea surface temperatures (SST) were studied in relation with the mucilage formation from January 2015 to August 2021 by using NOAA data. Two multispectral satellite sensors Sentinel-2 and Worldview-3 were studied for their potential for mucilage mapping and characterization in the sub-region Izmit Bay. Support vector machine (SVM) classifier was used to detect three different types of mucilage with distinguishable spectral differences in infrared region ranging from 725 to 950 nm. Three different types of mucilage were characterized based on color and texture including (a) the white mucilage aggregates with dispersed patterns which are likely freshly formed, (b) the yellow mucilage accumulations in the coasts that are wind/current transported, and (c) the brown mucilage accumulations that are probably the most-aged. Our results showed that brown mucilage and white mucilage showed similar reflectance values between 425 and 545 nm region, while yellow mucilage showed higher and more distinctive spectral reflectance than white and brown mucilages. The NOAA data showed that average surface water temperature has been increased over the years from 2015 (16.1 degrees C) to 2021 (17.6 degrees C). This increase trend in SSTs points out a likely relation with the mucilage formation and hence may suggest a potential of repeating mucilage events in the near future. This study provides a practical methodology for monitoring, classification, and efficient site selection for mucilage cleaning areas in the Sea of Marmara.