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AEROSOL PLUMES CHARACTERIZATION BY HYPERSPECTRAL IMAGES COUPLED WITH SENTINEL-2 PRODUCTS

机译:气溶胶羽毛特征在于高光谱图像与哨兵-2产品相结合

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In this paper, we focus on the retrieval of microphysical and optical properties of industrial aerosol plumes through a process using airborne hyperspectral and Sentinel-2 multi-spectral images. The process allows first to perform atmospheric correction and second to determine background aerosols thanks to a comparison between hyperspectral and Sentinel-2 reflectances. Hyperspectral methodologies use the radiance differential between the measurement in the plume and the corresponding measurements out of the plume to estimate plume properties. To retrieve the surface reflectance under the plume, a principal component analysis coupling hyperspectral and multispectral data class by class is achieved. The developed method aims to compare the difference between measured and estimated reflectance with a radiative transfer model accounting for plume properties (particle radius and aerosol optical thickness of the plume). We have applied the method to a steel plant in the south of France. The retrieved plume show an aerosol mean radius between 0.05 and 0.2 µm with a mean aerosol optical thickness about 0.05 along the plume.
机译:在本文中,我们专注于通过使用空气粗斑点和哨声-2多光谱图像的工艺来检索工业气溶胶羽毛的微孔和光学性质。该过程允许首先进行大气校正,并通过高光谱和哨声-2反射之间的比较来确定背景气溶胶。高光谱方法使用羽流量中的测量与羽流的相应测量之间的光线差异以估计羽流特性。为了在羽流下取回表面反射率,实现了耦合耦合高光谱和多光谱数据类的主成分分析。开发方法旨在比较测量和估计反射率之间的差异与羽毛特性(颗粒半径和羽流气溶胶光学厚度)的辐射转移模型核算。我们已经将该方法应用于法国南部的钢铁厂。检索的羽毛显示出0.05和0.2μm的气溶胶平均半径,平均气溶胶光学厚度约为0.05沿羽流。

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