The Use of Object-Based Image Analysis for Monitoring 2021 Marine Mucilage Bloom in the Sea of Marmara

Year 2021, Volume 8, Issue 4, 529 - 536, 15.12.2021

Taşkın KAVZOĞLU Hasan TONBUL İsmail ÇÖLKESEN Umut Gunes SEFERCİK

https://doi.org/10.30897/ijegeo.990875

Abstract

Global warming threatens ecosystems through rising temperatures, increasing sea levels, drought, and extreme weather conditions. The natural balance of seas and oceans is also at stake with recent outbreaks of mucilage events all over the world. The mucilage phenomenon, which has been frequently observed in the Adriatic and Tyrrhenian seas, has taken place the second time in the Sea of Marmara in Spring 2021. The Sea of Marmara dividing the Asian and European parts of Turkey is an important inland sea with heavy maritime traffic, hosting many industrial zones and surrounded by highly populated cities. This study aims to determine the mucilage formations that were observed intensely all around the Sea of Marmara, focusing on the coasts of Istanbul, Kocaeli, Yalova, and Bursa through classifying Sentinel-2A images dated 19 and 24 May 2021, when the peak period of mucilage bloom, using a new paradigm of object-based image analysis (OBIA) approach. To create representative and homogenous image objects, multi-resolution segmentation was applied, and its result was inputted into a classification process using Random Forest (RF) classifier to generate thematic maps. The produced results were compared with pixel-based classification and a high correlation was estimated. Object-based classification was found effective for the determination of mucilage-covered areas (> 90% overall accuracy) for both considered dates. More specifically, areas covered with mucilage aggregates were computed as 56.15 km² and 67.51 km² for 19 May and 24 May 2021, respectively, indicating rapid growth in only 5-day period. The resulting thematic maps revealed that mucilage was heavily distributed in the gulfs of Gemlik and Izmit and along the coasts of Darica, Tuzla and Pendik.

Keywords

Mucilage, OBIA, Random Forest, Segmentation, Sentinel-2A

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