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OIL SPILL DETECTION BY IMAGING RADARS: CHALLENGES AND PITFALLS

机译:成像雷达检测漏油:挑战和挑战

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Criteria for discriminating between radar signatures ofrnoil films and oil-spill look-alikes visible on syntheticrnaperture radar (SAR) images of the sea surface arerncritically reviewed. The main challenge in oil spillrndetection using SAR is to discriminate between mineralrnoil films and biogenic slicks originating from secretionsrn(exudations) of biota in the water column. The claimrnthat oil spill detection algorithms based on measuring 1)rnthe reduction of the normalized radar cross sectionrn(NRCS), 2) the differences in the geometry and shapernof the surface films, and 3) the differences in texturernhave a high success rate is questioned. Furthermore, it isrnquestioned that polarimetric SAR data are of great helprnfor discriminating between mineral oil films andrnbiogenic slicks. However, differences in the statisticalrnbehavior of the radar backscattering is expected due tornthe fact that, other than monomolecular biogenicrnsurface films, mineral oil films can form multi-layers.
机译:严格审查判别区分冰片的雷达信号和在海面的合成孔径雷达(SAR)图像上可见的溢油外观的标准。使用SAR进行溢油探测的主要挑战是区分矿物冰片和源自水柱中生物群分泌物(渗出物)的生物成因浮油。有人质疑基于以下方法的漏油检测算法:测量1)归一化雷达截面的减小(NRCS),2)几何形状和表面膜形状的差异,3)纹理的差异具有很高的成功率。此外,人们质疑极化SAR数据对于区分矿物油膜和生源浮油有很大帮助。但是,由于除单分子生物成因表面膜以外,矿物油膜还可以形成多层,因此可以预期雷达反向散射的统计行为会有所不同。

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