%A %T Quantitative Inversion of Organic Matter Content Based on Interconnection Traditional Spectral Transform and Continuous Wavelet Transform %0 Journal Article %D 2018 %J SPECTROSCOPY AND SPECTRAL ANALYSIS %R 10.3964/j.issn.1000-0593(2018)08-2571-07 %P 2571-2577 %V 38 %N 08 %U {https://www.gpxygpfx.com/CN/abstract/article_9997.shtml} %8 2018-08-01 %X In this study, the soil organic matter content of 96 alluvial soil collected from Beijing area was taken as the object of study; Compared with the traditional spectral transform technology, this paper studied on the analysis of the traditional spectral transform and continuous wavelet technology coupling in the feasibility of estimating soil organic matter content. Firstly, the traditional spectral transform technique and the continuous wavelet transform were used to deal with the soil spectral data. Then The correlation between the spectral data and the soil organic matter content was analyzed, and the sensitive bands were extracted. Finally the estimation model of soil organic matter content was constructed by partial least square method. The results showed that the coupling of traditional spectral transform and continuous wavelet technology can greatly improve the spectral sensitivity of organic matter content, and the correlation coefficient (R2) was up to 0.714, which indicate that the coupling of the traditional spectral transform and continuous wavelet technology can dig the useful signal of the spectral information; Compared with the traditional spectral transform technology, the accuracy of the model based on the interconnection of traditional technique and continuous wavelet transform was higher and better stability; Among of the model based on the interconnection of traditional technique and continuous wavelet transform, the model construct by the differential transform was the Optimal model; Its coefficient of decision and root mean square error were 0.774 and 0.223 respectively, which indicated that the interconnection of traditional technique and continuous wavelet transform spectral technique can effectively suppress noise, improving the spectral stability.