4.7 Article

Marine Oil Slick Detection Using Improved Polarimetric Feature Parameters Based on Polarimetric Synthetic Aperture Radar Data

期刊

REMOTE SENSING
卷 13, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/rs13091607

关键词

oil spill detection; polarimetric synthetic aperture radar; improved polarimetric feature parameters; different oil spill scenarios

资金

  1. National Key R&D Program of China [2020YFE0201500]
  2. Fundamental Research Funds for the Central Universities [3132014302, 3132019350]

向作者/读者索取更多资源

Marine oil spill detection is essential for emergency response and environmental recovery post-disaster. Pol-SAR technology can provide detailed information on oil slicks, look-alikes, and seawater scattering mechanisms. A novel polarimetric feature combination based on H and A efficiencies is proposed and proven to enhance oil slick distinguishability and suppress sea clutter.
Marine oil spill detection is vital for strengthening the emergency commands of oil spill accidents and repairing the marine environment after a disaster. Polarimetric Synthetic Aperture Radar (Pol-SAR) can obtain abundant information of the targets by measuring their complex scattering matrices, which is conducive to analyze and interpret the scattering mechanism of oil slicks, look-alikes, and seawater and realize the extraction and detection of oil slicks. The polarimetric features of quad-pol SAR have now been extended to oil spill detection. Inspired by this advancement, we proposed a set of improved polarimetric feature combination based on polarimetric scattering entropy H and the improved anisotropy A(12)-H_A(12). The objective of this study was to improve the distinguishability between oil slicks, look-alikes, and background seawater. First, the oil spill detection capability of the H_A(12) combination was observed to be superior than that obtained using the traditional H_A combination; therefore, it can be adopted as an alternate oil spill detection strategy to the latter. Second, H(1 - A(12)) combination can enhance the scattering randomness of the oil spill target, which outperformed the remaining types of polarimetric feature parameters in different oil spill scenarios, including in respect to the relative thickness information of oil slicks, oil slicks and look-alikes, and different types of oil slicks. The evaluations and comparisons showed that the proposed polarimetric features can indicate the oil slick information and effectively suppress the sea clutter and look-alike information.

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