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A Case Study of Dark-objects Subtraction based Atmospheric Correction Methods for GF-1 Satellite Images

机译:基于暗物减法的GF-1卫星图像大气校正方法研究

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In this study, two dark-object subtraction (DOS) based atmospheric correction methods were conducted for a GF-1 satellite image in 2016 over Guangzhou area, China. The effects of atmospheric correction were compared in two different domains, which are, ground reflectance and vegetation detection on the Normalized Difference Vegetation Index (NDVI). The obtained results show the DOS based atmospheric correction methods are effective for the GF-1 satellite images.
机译:在这项研究中,2016年对中国广州地区的GF-1卫星图像进行了两种基于暗物减法(DOS)的大气校正方法。在两个不同的领域中比较了大气校正的影响,这两个方面是地面反射率和植被检测对归一化植被指数(NDVI)的影响。获得的结果表明,基于DOS的大气校正方法对于GF-1卫星图像是有效的。

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