气候变化领域集成服务门户(CCPortal): Global spatiotemporally continuous MODIS land surface temperature dataset

CCPortal

DOI	10.1038/s41597-022-01214-8
	Global spatiotemporally continuous MODIS land surface temperature dataset
	Yu, Pei; Zhao, Tianjie; Shi, Jiancheng; Ran, Youhua; Jia, Li; Ji, Dabin; Xue, Huazhu
通讯作者	Zhao, TJ (通讯作者)，Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.
发表日期	2022
EISSN	2052-4463
卷号	9 期号:1
英文摘要	Land surface temperature (LST) plays a critical role in land surface processes. However, as one of the effective means for obtaining global LST observations, remote sensing observations are inherently affected by cloud cover, resulting in varying degrees of missing data in satellite-derived LST products. Here, we propose a solution. First, the data interpolating empirical orthogonal functions (DINEOF) method is used to reconstruct invalid LSTs in cloud-contaminated areas into ideal, clear-sky LSTs. Then, a cumulative distribution function (CDF) matching-based method is developed to correct the ideal, clear-sky LSTs to the real LSTs. Experimental results prove that this method can effectively reconstruct missing LST data and guarantee acceptable accuracy in most regions of the world, with RMSEs of 1-2 K and R values of 0.820-0.996 under ideal, clear-sky conditions and RMSEs of 4-7 K and R values of 0.811-0.933 under all weather conditions. Finally, a spatiotemporally continuous MODIS LST dataset at 0.05 degrees latitude/longitude grids is produced based on the above method.
关键词	POLAR ORBITING SATELLITES EDDY-COVARIANCE DIURNAL CYCLE RIVER-BASIN EVAPOTRANSPIRATION RECONSTRUCTION VALIDATION INTERPOLATION DROUGHT MODEL
语种	英语
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000777153400004
来源期刊	SCIENTIFIC DATA
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254437
作者单位	[Yu, Pei; Xue, Huazhu] Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo, Henan, Peoples R China; [Yu, Pei; Zhao, Tianjie; Jia, Li; Ji, Dabin] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing, Peoples R China; [Shi, Jiancheng] Chinese Acad Sci, Natl Space Sci Ctr, Beijing, Peoples R China; [Ran, Youhua] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Yu, Pei,Zhao, Tianjie,Shi, Jiancheng,et al. Global spatiotemporally continuous MODIS land surface temperature dataset[J]. 中国科学院西北生态环境资源研究院,2022,9(1).
APA	Yu, Pei.,Zhao, Tianjie.,Shi, Jiancheng.,Ran, Youhua.,Jia, Li.,...&Xue, Huazhu.(2022).Global spatiotemporally continuous MODIS land surface temperature dataset.SCIENTIFIC DATA,9(1).
MLA	Yu, Pei,et al."Global spatiotemporally continuous MODIS land surface temperature dataset".SCIENTIFIC DATA 9.1(2022).