Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3795-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-3795-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Aug 2024
Data description paper |
| 27 Aug 2024
| 27 Aug 2024
Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data
Bing Li
Key Research Institute of Yellow River Civilization and Sustainable Development & Laboratory of Climate Change Mitigation and Carbon Neutrality, Henan University, Zhengzhou 450046, China
Department of Geography, University of Hong Kong, Hong Kong SAR 999077, China
Department of Geography, University of Hong Kong, Hong Kong SAR 999077, China
Guanpeng Dong
Key Research Institute of Yellow River Civilization and Sustainable Development & Laboratory of Climate Change Mitigation and Carbon Neutrality, Henan University, Zhengzhou 450046, China
Xiaobang Liu
The 27th Research Institute of the China Electronics Technology Group Corporation, Zhengzhou 450047, China
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Yufang Zhang
School of Software, Northwestern Polytechnical University, Xi'an 710072, China
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Short summary
This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
This study describes 1 km all-weather instantaneous and daily mean land surface temperature...
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