中国30米纯像元归一化植被指数图集用于植被覆盖度估算（2014_2018_2022）

本研究利用多角度遥感数据，生成了中国全域30米空间分辨率的纯植被像元归一化植被指数（Vv）和纯土壤像元归一化植被指数（Vs）地图。这些像元级的Vv和Vs地图可与植被指数（VI）模型结合，支持不同空间分辨率和大范围区域的植被覆盖度（FVC）快速精确估算。
产品采用多角度算法（MultiVI）生成，该算法有效解决了Vv和Vs固有的空间变异性问题，与传统统计方法相比显著提高了FVC估算精度。在不同实验场地与实地测量FVC验证显示，估算的FVC均方根偏差（RMSD）约为0.1，表明产品具有较高的可靠性。

Using multi-angle remote sensing data, this study generated 30-meter spatial resolution maps of normalized difference vegetation index for pure vegetation pixels (Vv) and pure soil pixels (Vs) across the entire territory of China. These pixel-level Vv and Vs maps can be combined with vegetation index (VI) models to support rapid and accurate estimation of fractional vegetation cover (FVC) across large-scale regions with varying spatial resolutions. This dataset was produced using the multi-angle algorithm (MultiVI), which effectively addresses the inherent spatial variability of Vv and Vs, and significantly improves the accuracy of FVC estimation compared with conventional statistical methods. Validation against field-measured FVC at multiple experimental sites showed that the root mean square deviation (RMSD) of the estimated FVC is approximately 0.1, demonstrating the high reliability of this dataset.