Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product

doi:10.3390/rs11243025

	Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product
	Zhang, Shuting 1; Duan, Si-Bo 1; Li, Zhao-Liang 1,2; Huang, Cheng 1,3; Wu, Hua 2; Han, Xiao-Jing 1; Leng, Pei 1; Gao, Maofang 1
刊名	REMOTE SENSING
	2019-12-02
卷号	11 期号:24 页码:19
关键词	land surface temperature split-window algorithm temperature validation SLSTR ASTER GED
DOI	10.3390/rs11243025
通讯作者	Duan, Si-Bo(duansibo@caas.cn)
英文摘要	Land surface temperature (LST) is a key variable influencing the energy balance between the land surface and the atmosphere. In this work, a split-window algorithm was used to calculate LST from Sentinel-3A Sea and Land Surface Temperature Radiometer (SLSTR) thermal infrared data. The National Centers for Environmental Prediction (NCEP) reanalysis atmospheric profiles combined with the radiation transport model MODerate resolution atmospheric TRANsmission version 5.2 (MODTRAN 5.2) were utilized to obtain atmospheric water vapor content (WVC). The ASTER Global Emissivity Database Version 3 (ASTER GED v3) product was utilized to estimate surface emissivity in order to improve the accuracy of LST estimation over barren surfaces. Using a simulation database, the coefficients of the algorithm were fitted and the performance of the algorithm was evaluated. The root-mean-square error (RMSE) values of the differences between the estimated LST and the actual LST of the MODTRAN radiative transfer simulation at each WVC subrange of 0-6.5 g/cm(2) were less than 1.0 K. To validate the retrieval accuracy, ground-based LST measurements were collected at two relatively homogeneous desert study sites in Dalad Banner and Wuhai, Inner Mongolia, China. The bias between the retrieved LST and the in situ LST was about 0.2 K and the RMSE was about 1.3 K at the Dalad Banner site, whereas they were approximately -0.4 and 1.0 K at the Wuhai site. As a reference, the retrieved LST was compared with the operational SLSTR LST product in this study. The bias between the SLSTR LST product and the in situ LST was approximately 1 K and the RMSE was approximately 2 K at the Dalad Banner site, whereas they were approximately 1.1 and 1.4 K at the Wuhai site. The results demonstrate that the split-window algorithm combined with improved emissivity estimation based on the ASTER GED product can distinctly obtain better accuracy of LST over barren surfaces.
资助项目	National Natural Science Foundation of China[41871275] ; National Natural Science Foundation of China[41921001]
WOS关键词	EMISSIVITY RETRIEVAL ; ARID AREA ; COVER ; AATSR ; VIIRS ; NDVI
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000507333400139
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/131450]
专题	中国科学院地理科学与资源研究所
通讯作者	Duan, Si-Bo
作者单位	1.Chinese Acad Agr Sci, Key Lab Agr Remote Sensing, Minist Agr, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Shuting,Duan, Si-Bo,Li, Zhao-Liang,et al. Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product[J]. REMOTE SENSING,2019,11(24):19.
APA	Zhang, Shuting.,Duan, Si-Bo.,Li, Zhao-Liang.,Huang, Cheng.,Wu, Hua.,...&Gao, Maofang.(2019).Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product.REMOTE SENSING,11(24),19.
MLA	Zhang, Shuting,et al."Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product".REMOTE SENSING 11.24(2019):19.