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Proceedings Paper

Spectral feature extraction and modeling of soil total nitrogen content based on NIR technology and wavelet packet analysis
Author(s): Lihua Zheng; Minzan Li; Xiaofei An; Luan Pan; Hong Sun
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Paper Abstract

It is a non-destructive and real-time method to detect the soil nutrient content by using spectroscopy analysis technology. In order to isolate the effective spectral for TN content from the soil spectra effectively, the NIR model predicting TN was developed based on wavelet packet analysis. 100 soil samples were collected for calibration and validation from the field. First, using the high-precision NIR detecting instrument to scan the target and obtaining the continuous spectra of soil samples in the laboratory. Secondly, with three different orthogonal wavelets (bior4.4, db4, sym4) as the generating functions, the original signal of each soil sample was decomposed and reconstructed based on the respective wavelet packet. Then the multiple linear regression (MLR) models for TN were established based on each drawn characteristic spectrum. Finally, three models were compared and analyzed, and the model with the highest forecasting accuracy was obtained based on db4, which determined R2 reached 0.904. The research concluded that wavelet packet analysis could eliminate or substantially reduce the factors outside the parameters to the spectrum directly or indirectly, and the obstacles in establishing linear models for soil parameters were removed. It is feasible and potential to the real-time prediction of TN content.

Paper Details

Date Published: 16 November 2010
PDF: 8 pages
Proc. SPIE 7857, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III, 78571M (16 November 2010); doi: 10.1117/12.866220
Show Author Affiliations
Lihua Zheng, China Agricultural Univ. (China)
Minzan Li, China Agricultural Univ. (China)
Xiaofei An, China Agricultural Univ. (China)
Luan Pan, China Agricultural Univ. (China)
Hong Sun, China Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 7857:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III
Allen M. Larar; Hyo-Sang Chung; Makoto Suzuki, Editor(s)

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