Land-surface temperature retrieval from Landsat 8 single-channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product

doi:10.1080/01431161.2018.1460513

	Land-surface temperature retrieval from Landsat 8 single-channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product
	Duan, Si-Bo 1; Li, Zhao-Liang 1,2; Wang, Chenguang 3; Zhang, Shuting 1; Tang, Bo-Hui 2; Leng, Pei 1; Gao, Mao-Fang 1
刊名	INTERNATIONAL JOURNAL OF REMOTE SENSING
	2019
卷号	40 期号:5-6 页码:1763-1778
ISSN号	0143-1161
DOI	10.1080/01431161.2018.1460513
通讯作者	Li, Zhao-Liang(lizhaoliang@caas.cn)
英文摘要	Land-surface temperature (LST) is an important parameter in the climatological, hydrological, ecological, and meteorological studies. The Thermal Infrared Sensor (TIRS) on board the Landsat 8 is a key instrument to collect thermal infrared (TIR) data. The Landsat series sensors provide continuously acquired collection of space-based TIR data. In this study, we proposed a method for retrieving LST from Landsat 8 TIRS single-channel data. The National Centers for Environmental Prediction reanalysis data in conjunction with the Moderate Resolution Transmittance Code 5 were used to correct atmospheric effects. The ASTER Global Emissivity Database product was used to correct the effects of surface emissivity. In situ LST measurements were collected by eight and four SI-111 infrared radiometers in the study areas A and B, respectively. The in situ LST was used to validate the retrieved LST. For the study area A (sands), the bias varies from approximately -1.3 to 1.7K, and the root mean square error (RMSE) from approximately 1.2 to 2.1K. For the study area B (grasslands/snow), the bias ranges from approximately -1.0 to 0.4K, and the RMSE from approximately 1.1 to 1.5K. To further compare the retrieved LST and the in situ LST at coarser pixel scale, all of the retrieved LST and the in situ LST were, respectively, averaged as the corresponding LST at 1km pixel scale (e.g. Moderate Resolution Imaging Spectroradiometer). The biases of the differences between the two averaged LST at 1km pixel scale for all TIRS scenes are approximately -0.2 and -0.5K for the study areas A and B, respectively, and the RMSE values are approximately 1.2 and 1.0K for the study area A and B, respectively. These results indicate that the proposed method can be used to retrieve LST from single-channel TIR data with a reasonable accuracy.
资助项目	National Natural Science Foundation of China[41501406] ; National Natural Science Foundation of China[41231170]
WOS关键词	SPLIT-WINDOW ALGORITHM ; DIFFERENCE VEGETATION INDEX ; PHYSICS-BASED ALGORITHM ; ATMOSPHERIC CORRECTION ; MODIS DATA ; EMISSIVITY ; IMAGERY ; VALIDATION ; COVER ; WATER
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000464043900011
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/311030/48228]
专题	中国科学院地理科学与资源研究所
通讯作者	Li, Zhao-Liang
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, Peoples R China 3.Shanxi Univ, Sch Environm & Resources, Taiyuan, Shanxi, Peoples R China
推荐引用方式 GB/T 7714	Duan, Si-Bo,Li, Zhao-Liang,Wang, Chenguang,et al. Land-surface temperature retrieval from Landsat 8 single-channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019,40(5-6):1763-1778.
APA	Duan, Si-Bo.,Li, Zhao-Liang.,Wang, Chenguang.,Zhang, Shuting.,Tang, Bo-Hui.,...&Gao, Mao-Fang.(2019).Land-surface temperature retrieval from Landsat 8 single-channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product.INTERNATIONAL JOURNAL OF REMOTE SENSING,40(5-6),1763-1778.
MLA	Duan, Si-Bo,et al."Land-surface temperature retrieval from Landsat 8 single-channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product".INTERNATIONAL JOURNAL OF REMOTE SENSING 40.5-6(2019):1763-1778.