This article presents a comprehensive subpixel water mapping algorithm to automatically produce routinely open water fraction maps in the Tibetan Plateau (TP) with the Moderate Resolution Imaging Spectroradiometer (MODIS). A multi-index threshold endmember extraction method was applied to select the endmembers from MODIS images. To incorporate endmember variability, an endmember selection strategy, called the combined use of typical and neighboring endmembers, was adopted in multiple endmember spectral mixture analysis (MESMA), which can assure a robust subpixel water fractions estimation. The accuracy of the algorithm was assessed at both the local scale and regional scale. At the local scale, a comparison using the eight pairs of MODIS/Landsat 8 Operational Land Imager (OLI) water maps demonstrated that subpixels water fractions were well retrieved with a root mean square error (RMSE) of 7.86% and determination coefficient (R²) of 0.98. At the regional scale, the MODIS water fraction map in October 2014 matches well with the TP lake data set and the Global Lake and Wetland Database (GLWD) in both latitudinal and longitudinal distribution. The lake area estimation is more consistent with the reference TP lake data set (difference of −3.15%) than the MODIS Land Water Mask (MOD44W) (difference of −6.39%).

中文翻译：

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基于MODIS数据的青藏高原地表水亚像素制图。

本文提出了一种全面的亚像素水测图算法，该算法可使用中分辨率成像光谱仪（MODIS）自动生成青藏高原（TP）中的例行开放水分量图。应用多指标阈值末端成员提取方法从MODIS图像中选择末端成员。为了合并端成员的可变性，在多个端成员光谱混合分析（MESMA）中采用了称为典型和相邻端成员的组合的端成员选择策略，该策略可以确保可靠的子像素水分数估算。该算法的准确性是在本地规模和区域规模上进行评估的。在当地范围内²）为0.98。在区域尺度上，2014年10月的MODIS水分数图在横向和纵向分布方面与TP湖数据集和全球湖泊和湿地数据库（GLWD）相匹配。与MODIS陆水面罩（MOD44W）（−6.39％的差异）相比，湖泊面积的估算与TP湖参考数据集的差异（-3.15％）更一致。