Jing Yuhang, Niu Zhenguo
Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2025 Feb 18;25(4):1246. doi: 10.3390/s25041246.
The Tibetan Plateau, known as the "Third Pole" and the "Water Tower of Asia", has experienced significant changes in its surface water due to global warming. Accurately understanding and monitoring the spatiotemporal distribution of surface water is crucial for ecological conservation and the sustainable use of water resources. Among existing satellite data, the MODIS sensor stands out for its long time series and high temporal resolution, which make it advantageous for large-scale water body monitoring. However, its spatial resolution limitations hinder detailed monitoring. To address this, the present study proposes a dynamic endmember selection method based on phenological features, combined with mixed pixel decomposition techniques, to generate monthly water abundance maps of the Tibetan Plateau from 2000 to 2023. These maps precisely depict the interannual and seasonal variations in surface water, with an average accuracy of 95.3%. Compared to existing data products, the water abundance maps developed in this study provide better detail of surface water, while also benefiting from higher temporal resolution, enabling effective capture of dynamic water information. The dynamic monitoring of surface water on the Tibetan Plateau shows a year-on-year increase in water area, with an increasing fluctuation range. The surface water abundance products presented in this study not only provide more detailed information for the fine characterization of surface water but also offer a new technical approach and scientific basis for timely and accurate monitoring of surface water changes on the Tibetan Plateau.
被称为“第三极”和“亚洲水塔”的青藏高原,由于全球变暖,其地表水发生了显著变化。准确了解和监测地表水的时空分布对于生态保护和水资源的可持续利用至关重要。在现有的卫星数据中,MODIS传感器因其长时间序列和高时间分辨率而脱颖而出,这使其在大规模水体监测方面具有优势。然而,其空间分辨率的局限性阻碍了详细监测。为了解决这一问题,本研究提出了一种基于物候特征的动态端元选择方法,结合混合像元分解技术,生成了2000年至2023年青藏高原的月度水储量图。这些地图精确地描绘了地表水的年际和季节变化,平均精度为95.3%。与现有数据产品相比,本研究开发的水储量图提供了更好的地表水细节,同时受益于更高的时间分辨率,能够有效捕捉动态水信息。青藏高原地表水的动态监测显示,水域面积逐年增加,波动范围也在增大。本研究提出的地表水储量产品不仅为地表水的精细表征提供了更详细的信息,也为及时、准确地监测青藏高原地表水变化提供了一种新的技术方法和科学依据。