Hyperspectral estimation of soil heavy metals in Guanzhong area, Shaanxi province

Abstract

In this study, the contents of Cr, Mn, Ni, Cu, and Zn, As, Cd, Hg and Pub in 44 soil samples were collected from Fufeng County, Yangling County and Wugong County, Shaanxi Province and were used as data sources. ASD Field Spec HR (350 ∼ 2500 nm), and then the NOR, MSC and SNV of the reflectance were pretreated, the first deviation, second deviation and reflectance reciprocal logarithmic transformation were carried out. The optimal hyper spectral estimation model of nine heavy metal elements of Cr, Mn, Ni, Cu, and Zn, As, Cd, Hg and Pb was established by regression method. Comparing the reflection characteristics of different heavy metal contents and the effect of different pretreatment methods on the establishment of soil heavy metal spectral inversion model. The results show that: (1) the reflectance spectrum improves the signal-to-noise ratio of the reflectance spectrum after the transformation of NOR, MSC and SNV. Combining differential transformation can improve the information of heavy metal elements in the soil, and use the correlation band energy significantly improve the stability and predictability of the model. (2) The modeling accuracy of the optimal model of nine heavy metal spectra of Cr, Mn, Ni, Cu, and Zn, As, Cd, Hg and Pb by PLSR method were 0.7002, 0.7852, 0.687, 0.8036, 0.8619, 0.5765, 0.5451, 0.9912, and 0.6182.