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	A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data
	Leng, Pei1; Song, Xiaoning2; Duan, Si-Bo1; Li, Zhao-Liang1,3
刊名	International journal of applied earth observation and geoinformation
	2016-10-01
卷号	52页码:338-348
关键词	Surface soil moisture (ssm) Historical meteorological records Daily maximum solar radiation Optical and thermal infrared
ISSN号	0303-2434
DOI	10.1016/j.jag.2016.07.004
通讯作者	Li, zhao-liang(lizl@unistra.fr)
英文摘要	Surface soil moisture (ssm) is a critical variable for understanding the energy and water exchange between the land and atmosphere. a multi-linear model was recently developed to determine ssm using ellipse variables, namely, the center horizontal coordinate (x(0)), center vertical coordinate (y(0)), semi-major axis (a) and rotation angle (theta), derived from the elliptical relationship between diurnal cycles of land surface temperature (lst) and net surface shortwave radiation (nssr). however, the multi-linear model has a major disadvantage. the model coefficients are calculated based on simulated data produced by a land surface model simulation that requires sufficient meteorological measurements. this study aims to determine the model coefficients directly using limited meteorological parameters rather than via the complicated simulation process, decreasing the dependence of the model coefficients on meteorological measurements. with the simulated data, a practical algorithm was developed to estimate ssm based on combined optical and thermal infrared data. the results suggest that the proposed approach can be used to determine the coefficients associated with all ellipse variables based on historical meteorological records, whereas the constant term varies daily and can only be determined using the daily maximum solar radiation in a prediction model. simulated results from three fluxnet sites over 30 cloud-free days revealed an average root mean square error (rmse) of 0.042 m(3)/m(3) when historical meteorological records were used to synchronously determine the model coefficients. in addition, estimated ssm values exhibited generally moderate accuracies (coefficient of determination r-2 = 0.395, rmse = 0.061 m(3)/m(3)) compared to ssm measurements at the yucheng comprehensive experimental station. (c) 2016 elsevier b.v. all rights reserved.
WOS关键词	REMOTELY-SENSED DATA ; AMSR-E ; EMISSIVITY RETRIEVAL ; HYDROLOGICAL MODEL ; ERS SCATTEROMETER ; SATELLITE DATA ; TEMPERATURE ; SCALE ; INDEX ; WATER
WOS研究方向	Remote Sensing
WOS类目	Remote Sensing
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000383003500031
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2376271
专题	中国科学院大学
通讯作者	Li, Zhao-Liang
作者单位	1.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agriinformat, Minist Agr, Beijing 100081, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Stake Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Leng, Pei,Song, Xiaoning,Duan, Si-Bo,et al. A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data[J]. International journal of applied earth observation and geoinformation,2016,52:338-348.
APA	Leng, Pei,Song, Xiaoning,Duan, Si-Bo,&Li, Zhao-Liang.(2016).A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data.International journal of applied earth observation and geoinformation,52,338-348.
MLA	Leng, Pei,et al."A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data".International journal of applied earth observation and geoinformation 52(2016):338-348.

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