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An Improved 6S Code for Atmospheric Correction Based on Water Vapor Content

机译:基于水蒸气含量的大气校正改进的6S码

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Water vapor content in the atmosphere is very significant for atmospheric correction of optical remote sensing data. Nowadays, the common atmospheric correction models use a single value of the average water vapor content of the study area to perform atmospheric correction. As the distribution of water vapor content varies greatly with time and space, it is obviously inaccurate to represent the total water vapor conditions of the whole area by just reading the average water vapor content. In this study, we altered the 6S sources so that it could read the water vapor content image which was retrieved from MODIS 1 km data. Atmospheric correction was implemented for the band 1 of MODIS 500 m data pixel-by-pixel using the improved 6S model. In comparison with the traditional 6S model, this improved 6S model is more reasonable in atmospheric correction, for it considers the spatial distribution of the water vapor content retrieved from MODIS data in the near infrared to define the atmospheric conditions for simulating the atmospheric radiative transfer. The results corrected by the improved 6S model showed more reasonable in pixel spatial distribution and closer histogram with the original image than those by traditional 6S model.
机译:大气中的水蒸气含量对于光学遥感数据的大气校正非常重要。如今,常见的大气校正模型使用研究区域的平均水蒸气含量的单个值进行大气校正。由于水蒸气含量的分布随时间和空间而变化,因此通过只需读取平均水蒸气含量,显然不准确地表示整个区域的总水蒸汽条件。在这项研究中,我们改变了6S源,使得它可以读取从Modis 1km数据检索的水蒸汽含量图像。使用改进的6S模型为MODIS 500M数据像素的频带1实现了大气校正。与传统的6S模型相比,这种改进的6S模型在大气校正中更合理,因为它考虑了从近红外测量的Modis数据中检索的水蒸气内容的空间分布,以限定模拟大气辐射转移的大气条件。改进的6S模型所校正的结果显示在像素空间分布和更接近的直方图中,与原始图像更接近于传统6S模型。

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