Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

Area of Science:

• Environmental Science
• Remote Sensing Technology
• Marine Pollution Monitoring

Background:

• Oil spills pose significant threats to marine and coastal ecosystems, necessitating effective monitoring solutions.
• Evaluating seawater quality requires understanding pollutant discharge levels and their environmental impact.
• Satellite imagery provides a cost-effective and extensive method for continuous coastal surveillance.

Approach:

• This review comprehensively examines the application of Synthetic Aperture Radar (SAR) images for detecting illegal ship discharges.
• It summarizes current research and operational methodologies for oil spill detection using SAR data.
• The paper focuses on distinguishing oil spills from natural phenomena through manual and automatic approaches.

Key Points:

• SAR image analysis techniques for oil spill detection are reviewed.
• Common methods for identifying dark formations in SAR images are discussed.
• Feature extraction and classification methods for detected phenomena are detailed.

Conclusions:

• The review provides an overview of SAR-based oil spill detection methodologies.
• It highlights the importance of distinguishing spills from natural occurrences.
• Suggestions for future research directions are presented to advance the field.