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Updated: May 30, 2026

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
Published on: January 10, 2019
[Study of spectrum preprocessing method when applying the characteristic spectrum linear inversion modeling to
Fei Wang1, Qi-zhong Lin, Qin-jun Wang
1Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing. wangfei308@mails.gucas.ac.cn
Abstract:
The rapid identification of the minerals in the field is crucial in the remote sensing geology study and mineral exploration. The characteristic spectrum linear inversion modeling is able to obtain the mineral information quickly in the field study. However, the authors found that there was significant difference among the results of the model using the different kinds of spectra of the same sample. The present paper mainly studied the continuum based fast Fourier transform processing (CFFT) method and the characteristic spectrum linear inversion modeling (CSLM). On one hand, the authors obtained the optimal preferences of the CFFT method when applying it to rock samples: setting the CFFT low-pass frequency to 150 Hz. On the other hand, through the evaluation and study of the results of CSLM using different spectra, the authors found that the ASD spectra which were denoised in the CFFT method could provide better results when using them to extract the mineral information in the field.
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