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	Toward the estimation of surface soil moisture content using geostationary satellite data over sparsely vegetated area
	Leng, Pei1,2; Song, Xiaoning1; Li, Zhao-Liang2,3; Wang, Yawei1; Wang, Ruixin1
刊名	Remote sensing
	2015-04-01
卷号	7期号:4页码:4112-4138
ISSN号	2072-4292
DOI	10.3390/rs70404112
通讯作者	Song, xiaoning(songxn@ucas.ac.cn)
英文摘要	Based on a novel bare surface soil moisture (ssm) retrieval model developed from the synergistic use of the diurnal cycles of land surface temperature (lst) and net surface shortwave radiation (nssr) (leng et al. 2014. "bare surface soil moisture retrieval from the synergistic use of optical and thermal infrared data". international journal of remote sensing 35: 988-1003.), this paper mainly investigated the model's capability to estimate ssm using geostationary satellite observations over vegetated area. results from the simulated data primarily indicated that the previous bare ssm retrieval model is capable of estimating ssm in the low vegetation cover condition with fractional vegetation cover (fvc) ranging from 0 to 0.3. in total, the simulated data from the common land model (colm) on 151 cloud-free days at three fluxnet sites that with different climate patterns were used to describe ssm estimates with different underlying surfaces. the results showed a strong correlation between the estimated ssm and the simulated values, with a mean root mean square error (rmse) of 0.028 m(3)center dot m(-3) and a coefficient of determination (r-2) of 0.869. moreover, diurnal cycles of lst and nssr derived from the meteosat second generation (msg) satellite data on 59 cloud-free days were utilized to estimate ssm in the remedhus soil moisture network (spain). in particular, determination of the model coefficients synchronously using satellite observations and ssm measurements was explored in detail in the cases where meteorological data were not available. a preliminary validation was implemented to verify the msg pixel average ssm in the remedhus area with the average ssm calculated from the site measurements. the results revealed a significant r-2 of 0.595 and an rmse of 0.021 m(3)center dot m(-3).
WOS关键词	THERMAL INFRARED DATA ; EVAPOTRANSPIRATION ESTIMATION ; CANADIAN PRAIRIES ; WATER-BALANCE ; RETRIEVAL ; VALIDATION ; SPACE ; MODEL ; VARIABILITY ; DROUGHT
WOS研究方向	Remote Sensing
WOS类目	Remote Sensing
语种	英语
出版者	MDPI AG
WOS记录号	WOS:000354789300032
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2376513
专题	中国科学院大学
通讯作者	Song, Xiaoning
作者单位	1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 2.CNRS, ICube, UdS, F-67412 Illkirch Graffenstaden, France 3.Chinese Acad Agr Sci, Minist Agr, Key Lab Agri Informat, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Leng, Pei,Song, Xiaoning,Li, Zhao-Liang,et al. Toward the estimation of surface soil moisture content using geostationary satellite data over sparsely vegetated area[J]. Remote sensing,2015,7(4):4112-4138.
APA	Leng, Pei,Song, Xiaoning,Li, Zhao-Liang,Wang, Yawei,&Wang, Ruixin.(2015).Toward the estimation of surface soil moisture content using geostationary satellite data over sparsely vegetated area.Remote sensing,7(4),4112-4138.
MLA	Leng, Pei,et al."Toward the estimation of surface soil moisture content using geostationary satellite data over sparsely vegetated area".Remote sensing 7.4(2015):4112-4138.

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