In this feasibility study discriminating oil slicks and newly formed sea ice using synthetic aperture radar (SAR) imagery is investigated, using imagery from the L-band high-resolution uninhabited aerial vehicle synthetic aperture radar (UAVSAR) airborne and the satellite C-band RADARSAT-2 (RS-2) systems. To determine the separability of these two varying but similar appearing low backscatter ocean surfaces, multipolarization features are utilized from both SAR datasets. The discrimination is evaluated using the Kolmogorov–Smirnov separability test. All imagery was obtained during several sea ice campaigns in the Arctic Ocean and separate oil spill campaigns in Norway and the Gulf of Mexico, with each campaign collecting in situ observations. We observe that the polarization difference (VV-HH) reliably separates the mineral oil slicks and newly formed sea ice areas using UAVSAR images, due to the low noise floor and subsequent high signal-to-noise ratio (SNR) radiometric performance of the airborne system. The comparably higher noise floor and related lower SNR hampers the separability in the RS-2 images. Simulated noise floors were generated by adding white Gaussian noise to the UAVSAR data, which show that discrimination between the two low backscatter phenomena using multipolarization features is possible, provided that both datasets are still well above the noise floor. The pixel resolution has a limited effect on the separability. The results of this study provide an approach to distinguish oil slicks from newly formed sea ice, which might be of special interest should an oil spill occur within the marginal ice zone.

中文翻译：

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能否使用合成孔径雷达将矿物油层与新形成的海冰区分开来？

在这项可行性研究中，使用来自 L 波段高分辨率无人机合成孔径雷达 (UAVSAR) 机载和卫星 C 波段雷达卫星的图像，研究了使用合成孔径雷达 (SAR) 图像区分油膜和新形成的海冰-2 (RS-2) 系统。为了确定这两个不同但相似的低反向散射海洋表面的可分离性，利用了两个 SAR 数据集的多极化特征。使用 Kolmogorov-Smirnov 可分离性检验评估区分度。所有图像都是在北冰洋的几次海冰运动以及挪威和墨西哥湾的独立漏油运动中获得的，每次运动都收集现场观察结果。我们观察到偏振差 (VV-HH) 使用 UAVSAR 图像可靠地分离了矿物油膜和新形成的海冰区，这是由于机载的低噪声基底和随后的高信噪比 (SNR) 辐射测量性能。系统。相对较高的本底噪声和相关较低的 SNR 阻碍了 RS-2 图像的可分离性。通过向 UAVSAR 数据添加高斯白噪声来生成模拟的本底噪声，这表明使用多极化特征区分两种低反向散射现象是可能的，前提是两个数据集仍远高于本底噪声。像素分辨率对可分离性的影响有限。这项研究的结果提供了一种区分浮油和新形成的海冰的方法，