Articles | Volume 16, issue 1
https://doi.org/10.5194/essd-16-387-2024
https://doi.org/10.5194/essd-16-387-2024
Data description paper
 | 
17 Jan 2024
Data description paper |  | 17 Jan 2024

TRIMS LST: a daily 1 km all-weather land surface temperature dataset for China's landmass and surrounding areas (2000–2022)

Wenbin Tang, Ji Zhou, Jin Ma, Ziwei Wang, Lirong Ding, Xiaodong Zhang, and Xu Zhang

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Latest update: 04 Oct 2024
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Short summary
This paper reported a daily 1 km all-weather land surface temperature (LST) dataset for Chinese land mass and surrounding areas – TRIMS LST. The results of a comprehensive evaluation show that TRIMS LST has the following special features: the longest time coverage in its class, high image quality, and good accuracy. TRIMS LST has already been released to the scientific community, and a series of its applications have been reported by the literature.
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