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Inter-Comparison of Atmospheric Correction Methods on Sentinel-2 Images Applied to Croplands

机译:用于农田的Sentinel-2图像大气校正方法的相互比较

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Atmospheric correction of high resolution satellite scenery is a necessary preprocessing step for applications where bottom of atmosphere (BOA) reflectances are needed. The selection of the best atmospheric correction method to use on images acquired from new platforms, such as Sentinel-2, is essential to provide accurate BOA reflectances. In this work the performance of three atmospheric correction methods (6S, MAJA and SEN2COR) applied to Sentinel-2 scenes are compared by evaluating the resultant spectral signatures of six crop types on two specific dates, and their NDVI time series along a complete year. Although SEN2COR introduced greater corrections, especially in the infrared bands, the results suggest a varying performance of the methods depending on the land cover and the atmospheric conditions. Further research, particularly incorporating ground truth data, is recommended to rigorously validate the different atmospheric methods.
机译:对于需要大气底部(BOA)反射率的应用,高分辨率卫星风光的大气校正是必不可少的预处理步骤。选择最佳大气校正方法以用于从新平台(例如Sentinel-2)获取的图像上,对于提供准确的BOA反射率至关重要。在这项工作中,通过评估两种特定日期上六种作物的合成光谱特征及其一整年的NDVI时间序列,比较了应用于Sentinel-2场景的三种大气校正方法(6S,MAJA和SEN2COR)的性能。尽管SEN2COR引入了更大的校正,尤其是在红外波段,但结果表明该方法的性能取决于地面覆盖和大气条件。建议进一步研究,特别是结合地面实况数据,以严格验证不同的大气方法。

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