A mixing model for monitoring trace oil at sea

Huimin Lu, Yundong Han, Weili Liu
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Abstract

Oil spill has become one of the most serious marine pollution. Oil films gradually disperse into trace oil after accidents, still harmful to marine environment. It can cause various forms of direct harm to marine organisms, which is manifested in chronic toxicity. Accordingly, the amount of oil spilled into sea is of vital importance to environment protection. Airborne and spaceborne hyperspectral sensors are widely used for detecting and monitoring information such as human activities and environmental changes. Due to the limitation of spatial resolution, the spectral information is recorded as reflectance of a mixture of materials. Nonlinear interactions occur in the scene containing water. In order to extract the abundances of oil spills at sea, nonlinear mixture models have been developed. For trace oil, fractional abundance is at such a low order of magnitude that accurate description of the complex effect between oil and seawater remains a challenge. In this paper, a new mixing model is proposed to approximate the complex nonlinear interactions. It delivers a better understanding of the mixture in terms of trace oil as in-depth element in the seawater. Synthetic data is used to test the model. Experiment results show that unmixing with the proposed model leads to an accurate and stable fractional abundance distribution, even when oil abundance is at 06 level.
用于海上痕量油监测的混合模型
石油泄漏已成为最严重的海洋污染之一。事故发生后油膜逐渐分散成微量油,仍对海洋环境有害。它能对海洋生物造成多种形式的直接危害,主要表现为慢性毒性。因此,溢入海洋的石油量对环境保护至关重要。机载和星载高光谱传感器广泛应用于人类活动和环境变化等信息的探测和监测。由于空间分辨率的限制,光谱信息被记录为混合材料的反射率。非线性相互作用发生在含水的场景中。为了提取海上溢油的丰度,建立了非线性混合模型。对于微量油来说,分数丰度是如此之低,以至于准确描述油与海水之间的复杂影响仍然是一个挑战。本文提出了一种新的混合模型来近似复杂的非线性相互作用。它提供了一个更好地了解混合物的微量油作为海水中的深层元素。采用合成数据对模型进行检验。实验结果表明,当原油丰度为06级时,采用该模型解混得到的分数丰度分布准确、稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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