Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods

Yunus Emre Çukur; Ertürk Erdağı

doi:10.17798/bitlisfen.1773151

Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods

Abstract

Mucilage is an environmental problem that threatens biodiversity in marine ecosystems and poses socio-economic risks. In heavily polluted areas like the Marmara Sea, early detection of mucilage is crucial for maintaining ecological balance. Early detection allows policymakers to take swift action. This study utilizes deep learning methods to detect marine mucilage using satellite imagery. The study employed YOLOv7, YOLOv8, YOLOv11, and YOLOv12 models, along with transformer-based RF-DETR and Roboflow 3.0 architectures. A dataset comprising 1113 images from various satellite sources, with mucilage regions marked with bounding boxes, was used. The dataset was expanded using data enhancement techniques. The training process was improved by applying hyperparameters to all models, resulting in performance gains. The performance of the models used in the study was evaluated using precision, recall, mAP@0.5, and mAP@0.5:0.95 metrics. Experimental results show that the YOLOv8 model achieved higher success rates than other methods. Hyperparameter settings were found to significantly impact model performance. Evaluations indicate difficulties in mucilage detection due to low-resolution images and image complexity in coastal areas. This study demonstrates the applicability of artificial intelligence technologies for monitoring environmental problems and provides a decision-support infrastructure for early-warning systems.

Keywords

Ethical Statement

The study is complied with research and publication ethics.

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Details

Primary Language

English

Subjects

Artificial Intelligence (Other)

Journal Section

Research Article

Authors

Yunus Emre Çukur
0009-0007-8825-349X
Türkiye

Ertürk Erdağı ^*
0000-0001-8619-8879
Türkiye

Publication Date

December 31, 2025

Submission Date

August 28, 2025

Acceptance Date

December 21, 2025

Published in Issue

Year 2025 Volume: 14 Number: 4

DOI

https://doi.org/10.17798/bitlisfen.1773151

IZ

https://izlik.org/JA29BY54WX

Cite

RIS / Bibtex

APA

Çukur, Y. E., & Erdağı, E. (2025). Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 14(4), 2664-2683. https://doi.org/10.17798/bitlisfen.1773151

AMA

1.Çukur YE, Erdağı E. Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2025;14(4):2664-2683. doi:10.17798/bitlisfen.1773151

Chicago

Çukur, Yunus Emre, and Ertürk Erdağı. 2025. “Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 14 (4): 2664-83. https://doi.org/10.17798/bitlisfen.1773151.

EndNote

Çukur YE, Erdağı E (December 1, 2025) Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 14 4 2664–2683.

IEEE

[1]Y. E. Çukur and E. Erdağı, “Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, vol. 14, no. 4, pp. 2664–2683, Dec. 2025, doi: 10.17798/bitlisfen.1773151.

ISNAD

Çukur, Yunus Emre - Erdağı, Ertürk. “Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 14/4 (December 1, 2025): 2664-2683. https://doi.org/10.17798/bitlisfen.1773151.

JAMA

1.Çukur YE, Erdağı E. Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2025;14:2664–2683.

MLA

Çukur, Yunus Emre, and Ertürk Erdağı. “Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, vol. 14, no. 4, Dec. 2025, pp. 2664-83, doi:10.17798/bitlisfen.1773151.

Vancouver

1.Yunus Emre Çukur, Ertürk Erdağı. Detection and Comparative Analysis of Mucilage from Satellite Images Using Deep Learning Methods. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2025 Dec. 1;14(4):2664-83. doi:10.17798/bitlisfen.1773151