Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2555-2020
© Author(s) 2020. 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-12-2555-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Oct 2020
Data description paper |
| 27 Oct 2020
| 27 Oct 2020
A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003 to 2017
Bing Zhao
School of Physics and Electronic-Engineering, Ningxia University,
Yinchuan, 750021, China
Geomatics College, Shandong University of Science and Technology,
Qingdao, 266590, China
School of Physics and Electronic-Engineering, Ningxia University,
Yinchuan, 750021, China
Institute of Agricultural Resources and Regional Planning, Chinese
Academy of Agricultural Sciences, Beijing, 100081, China
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
Yulin Cai
Geomatics College, Shandong University of Science and Technology,
Qingdao, 266590, China
Jiancheng Shi
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
Zhaoliang Li
Institute of Agricultural Resources and Regional Planning, Chinese
Academy of Agricultural Sciences, Beijing, 100081, China
Zhihao Qin
Institute of Agricultural Resources and Regional Planning, Chinese
Academy of Agricultural Sciences, Beijing, 100081, China
Xiangjin Meng
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, 250100, China
Xinyi Shen
Civil and Environmental Engineering, University of Connecticut,
Storrs, CT 06269, USA
Zhonghua Guo
School of Physics and Electronic-Engineering, Ningxia University,
Yinchuan, 750021, China
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Latest update: 03 Nov 2024
Short summary
Land surface temperature is a key variable for climate and ecological environment research. We reconstructed a land surface temperature dataset (2003–2017) to take advantage of the ground observation site through building a reconstruction model which overcomes the effects of cloud. The reconstructed dataset exhibited significant improvements and can be used for the spatiotemporal evaluation of land surface temperature and for high-temperature and drought-monitoring studies.
Land surface temperature is a key variable for climate and ecological environment research. We...
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