Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-651-2022
https://doi.org/10.5194/essd-14-651-2022
Data description paper
 | 
15 Feb 2022
Data description paper |  | 15 Feb 2022

A global seamless 1 km resolution daily land surface temperature dataset (2003–2020)

Tao Zhang, Yuyu Zhou, Zhengyuan Zhu, Xiaoma Li, and Ghassem R. Asrar

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Latest update: 20 Nov 2024
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Short summary
We generated a global seamless 1 km daily (mid-daytime and mid-nighttime) land surface temperature (LST) dataset (2003–2020) using MODIS LST products by proposing a spatiotemporal gap-filling framework. The average root mean squared errors of the gap-filled LST are 1.88°C and 1.33°C, respectively, in mid-daytime and mid-nighttime. The global seamless LST dataset is unique and of great use in studies on urban systems, climate research and modeling, and terrestrial ecosystem studies.
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