Satellite-based vegetation indices are an essential element in understanding the Earth’s surface. In this study, we estimated the normalized difference vegetation index (NDVI) using Himawari-8/Advanced Himawari Imager (AHI) data and analyzed the sensitivity of products to atmospheric and surface correction. We used the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer model for atmospheric correction, and kernel-based semi-empirical bidirectional reflectance distribution function (BRDF) model to remove surface anisotropic effects. From this, top-of-atmosphere, top-of-canopy, and normalized NDVIs were produced. A sensitivity analysis showed that the normalized NDVI had the lowest number of missing values compared with the others and almost no low peaks during the study period. These results were validated by Terra and Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) and Project for On-Board Autonomy/Vegetation (PROBA) NDVI product, showing the root mean square error (RMSE) and bias of 0.09 and + 0.04 (MODIS) and 0.09 and − 0.04 (PROBA), respectively. These results also satisfied the FP7 Geoland2/BioPar project-defined user requirements (threshold: 0.15; target: 0.10).

中文翻译：

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通过Himawari-8 / AHI对考虑大气和BRDF校正的NDVI评估进行评估

基于卫星的植被指数是了解地球表面的基本要素。在这项研究中，我们使用Himawari-8 / Advanced Himawari Imager（AHI）数据估算了归一化植被指数（NDVI），并分析了产品对大气和表面校正的敏感性。我们使用太阳光谱（6S）辐射传输模型中的卫星信号的第二次模拟进行大气校正，并使用基于核的半经验双向反射率分布函数（BRDF）模型来消除表面各向异性效应。由此产生了大气层顶部，树冠层顶部和标准化的NDVI。敏感性分析表明，在研究期间，归一化NDVI的遗漏值数量最少，并且几乎没有低峰。这些结果已通过Terra和Aqua /中等分辨率成像光谱仪（MODIS）以及车载自主/植被（PROBA）NDVI产品项目进行了验证，显示均方根误差（RMSE）以及0.09和+ 0.04的偏差（MODIS）和0.09和-0.04（PROBA）。这些结果还满足了FP7 Geoland2 / BioPar项目定义的用户要求（阈值：0.15；目标：0.10）。