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Journal of Applied Remote Sensing

Estimating soil salt components and salinity using hyperspectral remote sensing data in an arid area of China
Author(s): Hongnan Jiang; Hong Shu; Lei Lei; Jianhui Xu
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Paper Abstract

HJ-1A hyperspectral data were used to distinguish topsoil salt components and estimate soil salinity, and the relationship between soil salt chemical components and sensitive bands of soil reflectance spectra was analyzed. The correlation between the soil salt content and the soil spectra obtained from the hyperspectral data was analyzed, proving that topsoil salinity has a very significant correlation with soil reflectance spectra. The relationship between soil reflectance spectra and salt chemical ions was investigated. The soil spectral reflectance at wavelength 510.975 nm and a difference vegetation index were selected to estimate soil salinity and the dominant salt chemical ion concentrations at a depth of 0 to 10 cm using a partial least squares regression model. It was found that the bands sensitive to various levels of chemical components of soil salt were shown to differ, controlled by the dominant component of the soil salt. The sensitive bands in the soil salinity estimation will change with differences in salt components. Estimating the dominant salt in the soil using soil reflectance spectra will lead to greater prediction accuracy. This study provided a possible method for the estimation of salinity and chemical component levels in topsoil, using the hyperspectral data to estimate topsoil salt components.

Paper Details

Date Published: 31 March 2017
PDF: 22 pages
J. Appl. Rem. Sens. 11(1) 016043 doi: 10.1117/1.JRS.11.016043
Published in: Journal of Applied Remote Sensing Volume 11, Issue 1
Show Author Affiliations
Hongnan Jiang, Wuhan Univ. (China)
Xinjiang Univ. (China)
Hong Shu, Wuhan Univ. (China)
Lei Lei, Xinjiang Univ. (China)
Jianhui Xu, Guangzhou Institute of Geography (China)

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