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Sensors 2018, 18(2), 376; https://doi.org/10.3390/s18020376

Estimation of the Land Surface Temperature over the Tibetan Plateau by Using Chinese FY-2C Geostationary Satellite Data

1,†
,
1,†,* , 2,3,4
,
1
,
1
,
1
and
5
1
Laboratory for Atmospheric Observation and Climate Environment Research, School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
2
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, the Chinese Academy of Sciences, Beijing 100101, China
3
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
4
University of Chinese Academy of Sciences, Beijing 100049, China
5
Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510080, China
These authors contributed equally to this study and shared first authorship.
*
Author to whom correspondence should be addressed.
Received: 6 December 2017 / Revised: 20 January 2018 / Accepted: 24 January 2018 / Published: 28 January 2018
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [6355 KB, uploaded 28 January 2018]   |  

Abstract

During the process of land–atmosphere interaction, one of the essential parameters is the land surface temperature (LST). The LST has high temporal variability, especially in its diurnal cycle, which cannot be acquired by polar-orbiting satellites. Therefore, it is of great practical significance to retrieve LST data using geostationary satellites. According to the data of FengYun 2C (FY-2C) satellite and the measurements from the Enhanced Observing Period (CEOP) of the Asia–Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet), a regression approach was utilized in this research to optimize the split window algorithm (SWA). The thermal infrared data obtained by the Chinese geostationary satellite FY-2C over the Tibetan Plateau (TP) was used to estimate the hourly LST time series. To decrease the effects of cloud, the 10-day composite hourly LST data were obtained through the approach of maximal value composite (MVC). The derived LST was used to compare with the product of MODIS LST and was also validated by the field observation. The results show that the LST retrieved through the optimized SWA and in situ data has a better consistency (with correlation coefficient (R), mean absolute error (MAE), mean bias (MB), and root mean square error (RMSE) values of 0.987, 1.91 K, 0.83 K and 2.26 K, respectively) than that derived from Becker and Li’s SWA and MODIS LST product, which means that the modified SWA can be applied to achieve plateau-scale LST. The diurnal variation of the LST and the hourly time series of the LST over the Tibetan Plateau were also obtained. The diurnal range of LST was found to be clearly affected by the influence of the thawing and freezing process of soil and the summer monsoon evolution. The comparison between the seasonal and diurnal variations of LST at four typical underlying surfaces over the TP indicate that the variation of LST is closely connected with the underlying surface types as well. The diurnal variation of LST is the smallest at the water (5.12 K), second at the snow and ice (5.45 K), third at the grasslands (19.82 K) and largest at the barren or sparsely vegetated (22.83 K). View Full-Text
Keywords: FengYun 2C; split window algorithm; land surface temperature; the Tibetan Plateau FengYun 2C; split window algorithm; land surface temperature; the Tibetan Plateau
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Hu, Y.; Zhong, L.; Ma, Y.; Zou, M.; Xu, K.; Huang, Z.; Feng, L. Estimation of the Land Surface Temperature over the Tibetan Plateau by Using Chinese FY-2C Geostationary Satellite Data. Sensors 2018, 18, 376.

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