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

机译:局部校正方法对田间校正方法的互相校正方法应用于农田

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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:高分辨率卫星风景的大气校正是用于大气(蟒蛇)反射底部的应用的必要预处理步骤。选择用于从新平台获取的图像的最佳大气校正方法,例如Sentinel-2,是提供准确的蟒蛇反射必不可少的。在这项工作中,通过评估两个特定日期的六种作物类型的所得谱签名,以及他们的NDVI时间序列,将应用于Sentinel-2场景的三种大气校正方法(6s,maja和sen2cor)的性能进行比较。虽然Sen2cor引入了更大的校正,特别是在红外条带中,但结果表明了根据陆地覆盖和大气条件的方法的变化性能。进一步的研究,特别是纳入地面真理数据,建议严格验证不同的大气方法。

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