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首页> 外文会议>Remote Sensing of Clouds and the Atmosphere XII; Proceedings of SPIE-The International Society for Optical Engineering; vol.6745 >Evaluation of adjacency effect for MIVIS airborne images
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Evaluation of adjacency effect for MIVIS airborne images

机译：MIVIS机载图像的邻接效应评估

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This work is aimed to atmospherically correct remote sensing data in the solar spectral domain (Visible and Near Infrared) allowing the better assessment of the surface spectral material characteristics. This was obtained by the inversion of the radiative transfer equation for at-sensor signal. In order to detect targets with peculiar spectral characteristics, the atmospheric correction has to take into account the diffuse radiation that constitutes a significant component to the at sensor radiance. The effect of this component (namely adjacency effect), which tends to mask the pixel seen by the sensor, derives principally from the atmospheric scattering due to the aerosol loading in the scene. At this purpose an algorithm based on 6S calculation was defined to derive the direct and diffuse component of the radiation required to determine the contribution to the pixel reflectance related to the surrounding pixels. The developed algorithm allowed the assessment of this environmental contribution besides the pixel reflectance. Such application, on airborne hyperspectral sensor MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) scenes, leads to obtain accurate pixel reflectance if compared with ground measurements acquired within testing areas. This work shows how adjacency effect has a significant role in the correction of remote sensing data, especially if acquired by an airborne hyperspectral sensor. The preliminary analysis of the results have highlighted that the adjacency effect is not negligible, mainly when pixels in the scene are spectrally heterogeneous.
机译：这项工作旨在对太阳光谱域（可见光和近红外）中的大气遥感数据进行大气校正，以便更好地评估表面光谱材料的特性。这是通过反演传感器信号的辐射传递方程获得的。为了检测具有特殊光谱特征的目标，大气校正必须考虑到构成辐射传感器辐射的重要组成部分的漫射辐射。倾向于掩盖传感器看到的像素的该分量的效应（即邻接效应）主要源自场景中气溶胶负载导致的大气散射。为此，定义了一种基于6S计算的算法，以得出确定与周围像素相关的像素反射率的贡献所需的辐射的直接分量和散射分量。除了像素反射率，开发的算法还可以评估这种环境贡献。与在测试区域内获取的地面测量值相比，这种应用在机载高光谱传感器MIVIS（多光谱红外和可见光成像光谱仪）场景上可获得准确的像素反射率。这项工作表明，邻近效应如何在遥感数据的校正中发挥重要作用，尤其是如果是通过机载高光谱传感器获取的话。对结果的初步分析突出表明，邻接效应不可忽略，主要是当场景中的像素在光谱上是异质的。

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