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Proceedings Paper

Quantitative inversion of soil sodium content and pH by hyperspectral remote sensing
Author(s): Jia-ge Chen; Tao Jiang; Qin-jun Wang; Yue Zhang; Hai-feng Ding; Zhang Huang
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Paper Abstract

Taking debris flow area as an example, this paper studied retrieval of soil Sodium content and pH by hyperspectral remote sensing, which provided a new method for estimating soil dispersion. Based on preprocessing, the authors extracted four spectral indices, including reflectance(R), inverse reflectance(1/R), inverse-log reflectance(log(1/R)) and band depth(BD), to establish the prediction model for Sodium content and pH using stepwise multiple regression method. Results indicated that reflectance spectra and inverse-log reflectance were the optimum parameters for inverting soil sodium ions content and pH, respectively. Determination coefficients R2 of prediction samples were 0.690 and 0.641 respectively, and R2 of test samples were 0.523 and 0.438, which showed that soil spectra with high spectral resolution had the potential for the rapid prediction of Sodium content and pH, thus, providing reliable detection method for soil dispersion using hyper-spectral technology.

Paper Details

Date Published: 26 November 2014
PDF: 9 pages
Proc. SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V, 92632U (26 November 2014); doi: 10.1117/12.2068371
Show Author Affiliations
Jia-ge Chen, Shandong Univ. of Science and Technology (China)
Tao Jiang, Shandong Univ. of Science and Technology (China)
Qin-jun Wang, Institute of Remote Sensing and Digital Earth (China)
Yue Zhang, Shandong Univ. of Science and Technology (China)
Hai-feng Ding, Institute of Remote Sensing and Digital Earth (China)
Zhang Huang, Institute of Remote Sensing and Digital Earth (China)


Published in SPIE Proceedings Vol. 9263:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)

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