Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection

doi:10.3390/app12020826

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	Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection
	J. Yuan; B. Yu; C. X. Yan; J. Q. Zhang; N. Ding and Y. Z. Dong
刊名	Applied Sciences-Basel
	2022
卷号	12 期号:2 页码:11
DOI	10.3390/app12020826
英文摘要	Featured Application In this study, a joint selection method of sensitive wavelength, optimal spectral resolution and signal-to-noise ratio of soil water content is proposed, which comprehensively considers the joint influence of spectral wavelength, spectral resolution and signal-to-noise ratio on the inversion accuracy. The method proposed in this paper can also be used to select the sensitive wavelength, optimal spectral resolution and signal-to-noise ratio of soil organic matter. It is found that the remote sensing parameters such as spectral range, spectral resolution and signal-to-noise ratio directly affect the estimation accuracy of soil moisture content. However, the lack of research on the relationship between the parameters and estimation accuracy restricts the prolongation of application. Therefore, this study took the demand for this application as the foothold for developing spectrometry. Firstly, a method based on sensitivity analysis of soil radiative transfer model-successive projection algorithm (SA-SPA) was proposed to select sensitive wavelengths. Then, the spectral resampling method was used to select the best spectral resolution in the corresponding sensitive wavelengths. Finally, the noise-free spectral data simulated by the soil radiative transfer model was added with Gaussian random noise to change the signal-to-noise ratio, so as to explore the influence of signal-to-noise ratio on the estimation accuracy. The research results show that the estimation accuracy obtained through the SA-SPA (RMSEP < 12.1 g kg(-1)) is generally superior to that from full-spectrum data (RMSEP < 14 g kg(-1)). At selected sensitive wavelengths, the best spectral resolution is 34 nm, and the applicable signal-to-noise ratio ranges from 150 to 350. This study provides technical support for the efficient estimation of soil moisture content and the development of spectrometry, which comprehensively considers the common influence of spectral range, spectral resolution and signal-to-noise ratio on the estimation accuracy of soil moisture content.
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语种	英语
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/67113]
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,B. Yu,C. X. Yan,et al. Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection[J]. Applied Sciences-Basel,2022,12(2):11.
APA	J. Yuan,B. Yu,C. X. Yan,J. Q. Zhang,&N. Ding and Y. Z. Dong.(2022).Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection.Applied Sciences-Basel,12(2),11.
MLA	J. Yuan,et al."Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection".Applied Sciences-Basel 12.2(2022):11.