干旱区生态环境知识资源中心(Arid): Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation

Arid

DOI	10.3964/j.issn.1000-0593(2022)04-1278-07
	Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation
	Yumiti Maiming; Wang Xue-mei
通讯作者	Wang, XM
来源期刊	SPECTROSCOPY AND SPECTRAL ANALYSIS
ISSN	1000-0593
出版年	2022
卷号	42 期号:4 页码:1278-1284
英文摘要	The hyperspectral estimation of soil organic matter content can quickly and accurately monitor soil fertility and provide a scientific basis for proper fertilization of modern agricultural production. Taking the cultivated soil in the delta oasis of Weigan-Kuqa river, Xinjiang as the research object, the original spectral reflectance (R) of the collected 98 soil samples was subjected to the traditional reciprocal logarithm 1g(1/R), the first-order differential (R') and the reciprocal logarithm first-order differential [1g(1/R)]' mathematical transformations, and continuous wavelet transformation (Continuous Wavelet Transformation, CWT) processing based on Bior1.3 as the wavelet mother function through different scale decomposition. Correlation analysis was conducted between the treatment results and the measured soil organic matter content to screen out the characteristic bands and wavelet coefficients closely related to soil organic matter content under various transformations (p<0.01). With the original spectral reflectance, the characteristic band reflectance and the sensitive wavelet coefficient under different transformation treatments as independent variables and the soil organic matter content as dependent variables, partial least squares regression and support vector machine regression was used to estimate models of soil organic matter content. The results showed that; (1) Various spectral transformation methods can effectively improve the sensitivity between the spectrum and the content of soil organic matter. The correlation between the soil spectral reflectance and the organic matter content after continuous wavelet transformation has been significantly improved, and the correlation coefficient has been increased from 0.39 to 0.54 (p<0.01). (2) The support vector machine regression model built by the traditional [1g(1/R)]' transformation has a higher coefficient of determination (R') than the model built by 1g(1/R) and R' transformation, showing the reciprocal logarithm first-order differential transformation can help improve the accuracy of the estimation model, and the accuracy and stability of the support vector machine regression model were higher than that of the partial least squares regression model. (3) After continuous wavelet transformation decomposition, the estimation accuracy and stability of the models were obviously improved by using the sensitive wavelet coefficients of the original spectral reflectance at different scales as independent variables. The decision coefficient (R-2), root mean square error (RMSE) and relative analysis error (RPD) of the CWT-23-SVMR model were 0.84, 1.48 and 2.11 respectively. The model has the highest accuracy and excellent predictive ability. After multiple transformation processing, hyperspectral data can effectively remove white noise. In contrast, continuous wavelet transformation processing is more suitable for mining effective soil information than the traditional mathematical transformation method, to realize the effective separation of approximate features and detailed features of spectral signals, and the established inversion model can more accurately estimate soil organic matter content.
英文关键词	Continuous wavelet transformation Hyperspectral estimation Decomposition scale Soil organic matter The delta oasis of Weigan-Kuqa rivers
类型	Article
语种	中文
收录类别	SCI-E
WOS记录号	WOS:000791027500044
WOS类目	Spectroscopy
WOS研究方向	Spectroscopy
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394531
推荐引用方式 GB/T 7714	Yumiti Maiming,Wang Xue-mei. Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation[J],2022,42(4):1278-1284.
APA	Yumiti Maiming,&Wang Xue-mei.(2022).Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation.SPECTROSCOPY AND SPECTRAL ANALYSIS,42(4),1278-1284.
MLA	Yumiti Maiming,et al."Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation".SPECTROSCOPY AND SPECTRAL ANALYSIS 42.4(2022):1278-1284.