Detection of Chlorophyll A on the Black Sea Coast with Sentinel-2 Satellite

Yıl 2023, Cilt: 7 Sayı: 1, 48 - 56, 30.06.2023

Nehir Uyar Aycan Murat Marangoz Sefa Kocabaş Sabri Mutlu Hakan Atabay

https://doi.org/10.32571/ijct.1201634

Öz

It is costly and time-consuming to determine coastal pollution with ground measurements. One of the most basic parameters to determine pollution in these areas is Chlorophyll A. This study aims to investigate the determination of this parameter using Remote Sensing (RS) techniques. In the study, the Sentinel-2 satellite was used to determine the parameter Chlorophyll A in the coastal areas of the Black Sea. 19 algorithms were used in the application. The algorithms are related to luminance reflections and the 8 bands of the satellite were used for the study. An Artificial Neural Network model was published as the best result. Pollution was observed in the coastal areas of the Black Sea between 2021 and 2017. As a result of the analysis, it is possible to observe coastal pollution quickly, without cost and/or at very low cost, with RS techniques. In this sense, RS techniques are of great importance in detecting environmental pollution, and relevant algorithms should be developed and supported by local measurements.

Anahtar Kelimeler

Chlorophyll a, Remote Sensing, Sentinel 2, Artificial Neural Network Model, pollution

Teşekkür

The authors thank the “Integrated Marine Pollution Monitoring 2017–2021 Program” funded by the Turkish Ministry of Environment and Urbanization/General Directorate of EIA, Permit and Inspection/ Department of Laboratory, Measurement and coordinated by TUBITAK- MRC CC&S for the provisioning of the data used in this study. We thank all the crew of R/V TÜBİTAK MARMARA and the Marine Research & Technologies Group

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