首页> 外文会议>ISPRS Geospatial Week >ESTIMATION OF THE THICKNESS AND EMULSION RATE OF OIL SPILLED AT SEA USING HYPERSPECTRAL REMOTE SENSING IMAGERY IN THE SWIR DOMAIN
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ESTIMATION OF THE THICKNESS AND EMULSION RATE OF OIL SPILLED AT SEA USING HYPERSPECTRAL REMOTE SENSING IMAGERY IN THE SWIR DOMAIN

机译:SWIR结构遥感图像在海上溢出的厚度和乳液速率的估算

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The thickness and the emulsion rate of an oil spill are two key parameters allowing to design a tailored response to an oil discharge. If estimated on per pixel basis at a high spatial resolution, the estimation of the oil thickness allows the volume of pollutant to be estimated, and that volume is needed in order to evaluate the magnitude of the pollution, and to determine the most adapted recovering means to use. The estimation of the spatial distribution of the thicknesses also allows the guidance of the recovering means at sea. The emulsion rate can guide the strategy to adopt in order to deal with an offshore oil spill: efficiency of dispersants is for example not identical on a pure oil or on an emulsion. Moreover, the thickness and emulsion rate allow the amount of the oil that has been discharged to be estimated. It appears that the shape of the reflectance spectrum of oil in the SWIR range (1000-2500nm) varies according to the emulsion rate and to the layer thickness. That shape still varies when the oil layer reaches a few millimetres, which is not the case in the visible range (400-700nm), where the spectral variation saturates around 200 μm (the upper limit of the Bonn agreement oil appearance code). In that context, hyperspectral imagery in the SWIR range shows a high potential to describe and characterize oil spills. Previous methods which intend to estimate those two parameters are based on the use of a spectral library. In that paper, we will present a method based on the inversion of a simple radiative transfer model in the oil layer. We will show that the proposed method is robust against another parameter that affects the reflectance spectrum: the size of water droplets in the emulsion. The method shows relevant results using measurements made in laboratory, equivalent to the ones obtained using methods based on the use of a spectral library. The method has the advantage to release the need of a spectral library, and to provide maps of thickness and emulsion rate values per pixel. The maps obtained are not composed of regions of thickness ranges, such as the ones obtained using discretized levels of measurements in the spectral library, or maps made from visual observations following the Bonn agreement oil appearance code.
机译:溢油的厚度和乳液率是两个关键参数,允许设计对油气排出的定制响应。如果在高空间分辨率下估计每个像素,则油厚度的估计允许估计污染物的体积,并且需要该体积以评估污染的大小,并确定最适应最适应的恢复手段使用。厚度的空间分布的估计也允许在海上的回收装置的引导。乳液率可以指导策略采用,以处理海上溢油:分散剂的效率例如在纯油或乳液上不相同。此外,厚度和乳液速率允许估计已经排出的油的量。似乎SWIR范围(1000-2500nm)中的油的反射光谱的形状根据乳液速率和层厚度而变化。当油层达到几毫米时,这种形状仍然变化,这不是可见范围(400-700nm)的情况,其中光谱变化饱和约200μm(波恩协议油外观代码的上限)。在这种情况下,SWIR范围内的高光谱图像显示出描述和表征溢油的高潜力。预先估计这两个参数的先前方法基于使用光谱库。在该论文中,我们将提出一种基于油层中简单辐射转移模型的反演的方法。我们将表明,该方法对抗影响反射光谱的另一个参数是强大的:乳液中的水滴的尺寸。该方法显示了使用实验室中的测量结果的相关结果,其等于使用基于使用光谱库的方法获得的结果。该方法具有释放光谱库的需要的优点,并提供每个像素的厚度和乳液率值的图。所获得的地图不是由厚度范围的区域组成,例如在光谱库中使用离散化测量水平获得的地图,或由波恩协议油外观代码之后的视觉观测所做的地图。

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