Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响，使得传感器接收到的辐射信号既包含了地物的信息，同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度，需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法，该方法由6S辐射传输模型生成查找表，其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素，这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表，对于Landsat-8 OLI传感器具有很高的通用性，通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后，采用目视解译、统计分析将校正结果与SEVI做对比分析，比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。

Atmospheric Correction of Landsat-8 Satellite Image and Its Vegetation Index Comparison with SEVI

remote sensing images are affected by the atmospheric absorption, scattering and topographic changes, so that the radiation signals received by the sensors contain both the information of the ground features and the information of the atmosphere and terrain.In order to improve the retrieval accuracy of land surface reflectance, remote sensing images need to be pretreated.In this paper, a method of atmospheric correction for Landsat8 remote sensing images based on Look-Up Table（LUT） is proposed.The method generates LUT by the 6S radiative transfer model, in which the input parameters include water vapor content, ozone concentration, and aerosol optical depth (AOT) retrieved from the MODIS atmospheric two stage product.The atmospheric parameter table established by traditional method usually considers only a few factors, which is not applicable to atmospheric correction using MODIS product as input parameter.Therefore, this paper established a five dimensional LUT most of the input parameters, with high generality for Landsat-8 OLI sensor, and spectral analysis, to verify the the accuracy of the model of USGS surface reflectance products. The correlation (R²) between model-based NDVI and USGS-based NDVI was as high as 0.802 6.The verification results show that the method can effectively accurate inversion of surface reflectance products. It is also found that the calculated NDVI based on 6S radiation transmission model is more in line with the spectral characteristics of typical vegetation than the NDVI based on apparent reflectance. Finally, using visual interpretation, statistical analysis and Shadow-eliminated Vegetation Index(SEVI) correction results will do comparative analysis, compare the terrain subtractive effect. The results show that the 6S radiative transfer model and SEVI have little difference in the effect of terrain attenuation.