Study on Soil Salinization Based on GIS and RS

Abstract:

This paper obtained the surface reflectance image by using FLAASH atmospheric correction model to conduct atmospheric correction to the HSI image. After the reflectance image was processed with multi mathematical manipulations, the analytical method of geographic information system (GIS) was applied to carry out the partial least squares regression (PLSR) analysis with the measured value of soil salinity, thus quantitatively inverting the soil salinity in Songliao Plain. The research result indicated that the reflectance of HSI hyperspectral imaging can increase the related coefficient R² of salt content in saline alkali soil significantly after being processed with reciprocal (1/R) and first-order differentiation (R), reaching 0.818 and 0.851 respectively with a root mean square error (RMSE) of 0.77 and 0.694 respectively, quantitatively and quickly gaining the soil salinity in Songliao Plain as well as salinization prevention.

• Periodical: Applied Mechanics and Materials (Volumes 333-335)
• Pages: 81-85
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.333-335.81
• Online since: July 2013
• Authors: Chi Ma
• Keywords: Environment Satellite, Partial Least Squares Regression, Quantitative Inversion, Resource, Saline-Alkali Soil

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