The Tibetan Plateau, known as the “Asian Water Tower”, contains thousands of lakes that are sensitive to climate variability and human activities. To investigate their long-term and short-term dynamics, we developed a daily surface-water mapping dataset covering the period from 2000 to 2024 based on MODIS daily reflectance time series (MOD09GQ/MYD09GQ and MOD09GA/MYD09GA). A hybrid methodology combining per-pixel spectral indices, superpixel segmentation, and fusion of Terra and Aqua results was applied, followed by temporal interpolation to produce cloud-free daily water maps. Validation against Landsat classifications and the 30 m global water dataset indicates an overall accuracy of 96.89% and a mean relative error below 9.1%, confirming the robustness of our dataset. Based on this dataset, we analyzed the spatiotemporal evolution of 1293 lakes (no less than 5 km2). Results show that approximately 87.7% of lakes expanded, with the fastest growth reaching +43.18 km2/y, whereas 12.3% shrank, with the largest decrease being −5.91 km2/y. Seasonal patterns reveal that most lakes reach maximum extent in October and minimum extent in January. This study provides a long-term, cloud-free daily water mapping product for the Tibetan Plateau, which can serve as a valuable resource for future research on regional hydrology, ecosystem vulnerability, and climate–water interactions in high-altitude regions.
Feng et al. (Tue,) studied this question.