Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information

doi:10.3390/rs11030366

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所

	Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information
	J.Yuan; X.Wang; C.X.Yan; S.R.Wang; X.P.Ju; Y.Li
刊名	Remote Sensing
	2019
卷号	11 期号:3 页码:17
关键词	hyperspectral remote sensing,soil moisture retrieval model,reflectance,semi-empirical model,Water,spectroscopy,prediction,spectra,Remote Sensing
DOI	10.3390/rs11030366
英文摘要	The variation and the spatial-temporal distribution of soil water content have significant effects on heat balance, agricultural moisture, etc. A soil moisture (SM) retrieval model can provide a theoretical basis for realizing a rapid test and revealing the spatial-temporal variation of the surface water. However, remote sensors do not measure soil water content directly. Therefore, it is of great importance to establish a SM retrieval model. In this paper, the relationship between SM and diffuse reflectance was first derived using the absorption coefficient and scattering coefficient related to SM. Then, based on Kubelka-Munk (KM) theory, the SM retrieval model using reflectance information was further derived, which is a semi-empirical model with an unknown parameter obtained either from fitting or from experimental measurements. The validity and reliability of the model were confirmed with the validation set. The results showed that the root mean square errors of prediction (RMSEPs) of four soils were generally less than 0.017, while the coefficients of determination (R(2)s) of four soils were generally more than 0.85, and the ratios of the performance to deviation (RPDs) of four soils were greater than 2.5 (470-2400 nm). Therefore, the model has high prediction accuracy, and can be well applied to the prediction of water content in different sorts of soils.
语种	英语
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/62837]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	J.Yuan,X.Wang,C.X.Yan,et al. Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information[J]. Remote Sensing,2019,11(3):17.
APA	J.Yuan,X.Wang,C.X.Yan,S.R.Wang,X.P.Ju,&Y.Li.(2019).Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information.Remote Sensing,11(3),17.
MLA	J.Yuan,et al."Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information".Remote Sensing 11.3(2019):17.