DOI: 10.1016/j.jag.2016.07.004
Scopus记录号: 2-s2.0-84997796177
论文题名: A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data
作者: Leng P ; , Song X ; , Duan S ; -B ; , Li Z ; -L
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 52 起始页码: 338
结束页码: 348
语种: 英语
英文关键词: Daily maximum solar radiation
; Historical meteorological records
; Optical and thermal infrared
; Surface soil moisture (SSM)
Scopus关键词: algorithm
; infrared spectroscopy
; land surface
; meteorology
; shortwave radiation
; soil moisture
; solar radiation
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 (x0), center vertical coordinate (y0), semi-major axis (a) and rotation angle (θ), 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 m3/m3 when historical meteorological records were used to synchronously determine the model coefficients. In addition, estimated SSM values exhibited generally moderate accuracies (coefficient of determination R2 = 0.395, RMSE = 0.061 m3/m3) compared to SSM measurements at the Yucheng Comprehensive Experimental Station. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80047
Appears in Collections: 气候变化事实与影响
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作者单位: Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China; Stake Key Laboratory of Resources and Environmmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Recommended Citation:
Leng P,, Song X,, Duan S,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,2016-01-01,52