Publications by authors named "Yuanlin Qiu"

Lakes play a crucial role in shaping both local and regional climates through heat exchange with the atmosphere. Amid global climate change, these interactions have undergone significant shifts. However, our understanding of the global heat release from lakes to the atmosphere, and its future trajectory, remains limited.

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The accurate and timely monitoring of the soil salt content (SSC) at different depths is the prerequisite for the solution to salinization in the arid and semiarid areas. Sentinel-2 has demonstrated significant superiority in SSC inversion for its higher temporal, spatial and spectral resolution, but previous research on SSC inversion with Sentinel-2 mainly focused on the unvegetated surface soil. Based on Sentinel-2 data, this study aimed to build four machine learning models at five depths (0∼20 cm, 20∼40 cm, 40∼60 cm, 0∼40 cm, and 0∼60 cm) in the vegetated area, and evaluate the sensitivity of Sentinel-2 to SSC at different depths and the inversion capability of the models.

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