Abstract
Global warming together with environmental pollution threatens marine habitats and causes an increasing number of environmental disasters. Periodic monitoring of coastal water quality is of critical importance for the effective management of water resources and the sustainability of marine ecosystems. The use of remote sensing technologies provides significant benefits for detecting, monitoring, and analyzing rapidly occurring and displaced natural phenomena, including mucilage events. In this study, five water indices estimated from cloud-free and partly cloudy Sentinel-2 images acquired from May to July 2021 were employed to effectively map mucilage aggregates on the sea surface in the Izmit Bay using the cloud-based Google Earth Engine (GEE) platform. Results showed that mucilage aggregates started with the coverage of about 6 km² sea surface on 14 May, reached the highest level on 24 May and diminished at the end of July. Among the applied indices, the Adjusted Floating Algae Index (AFAI) was superior for producing the mucilage maps even for the partly cloudy image, followed by Normalized Difference Turbidity Index (NDTI) and Mucilage Index (MI). To be more specific, indices using green channel were found to be inferior for extracting mucilage information from the satellite images.
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