Log Transformed Coherency Matrix for Differentiating Scattering Behaviour of Oil Spill Emulsions Using SAR Images

Kinjal Prajapati, Ratheesh Ramakrishnan, Madhuri Bhavsar, Alka Mahajan, Zunnun Narmawala, Archana Bhavsar, Maria Simona Raboaca and Sudeep Tanwar
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Kinjal Prajapati: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India
Ratheesh Ramakrishnan: Space Application Center, ISRO, Ahmedabad 380015, India
Madhuri Bhavsar: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India
Alka Mahajan: SVKM’s Mukesh Patel School of Technology, Management, and Engineering, Mumbai 400056, India
Zunnun Narmawala: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India
Archana Bhavsar: Department of Computer Engineering, SSBT’S College of Engineering and Technology, Bambhori, Jalgaon 425001, India
Maria Simona Raboaca: National Research and Development Institute for Cryogenic and Isotopic Technologies—ICSI Râmnicu Valcea, Uzinei Street, No. 4, P.O. Box 7 Raureni, 240050 Râmnicu Vâlcea, Romania
Sudeep Tanwar: Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India

Mathematics, 2022, vol. 10, issue 10, 1-22

Abstract: Oil spills on the ocean surface are a serious threat to the marine ecosystem. Automation of oil spill detection through full/dual polarimetric Synthetic Aperture Radar (SAR) images is considered a good aid for oil spill disaster management. This paper uses the power of log transformation to discern the scattering behavior more effectively from the coherency matrix (T3). The proposed coherency matrix is tested on patches of the clean sea surface and four different classes of oil spills, viz. heavy sedimented oil, thick oil, oil-water emulsion, fresh oil; by analyzing the entropy ( H ), anisotropy ( A ), and mean scattering angle alpha ( α ), following the H / A / α decomposition. Experimental results show that not only does the proposed T3 matrix differentiate between Bragg scattering of the clean sea surface from a random scattering of thick oil spills but is also able to distinguish between different emulsions of oil spills with water and sediments. Moreover, unlike classical T3, the proposed method distinguishes concrete-like structures and heavy sedimented oil even though both exhibit similar scattering behavior. The proposed algorithm is developed and validated on the data acquired by the UAVSAR full polarimetric L band SAR sensor over the Gulf of Mexico (GOM) region during the Deepwater Horizon (DWH) oil spill accident in June 2010.

Keywords: oil spill detection; UAVSAR; Deep Water Horizon; weathered oil; oil characterization; SAR Polarimetry (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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