Salinity Monitoring at Saline Sites with Visible–Near-Infrared Spectral Data

Abstract

To address the global phenomenon of the salinisation of large land areas, a quantitative inversion model of the salinity of saline soils and soil visible–near-infrared (NIR) spectral data was developed by considering saline soils in Zhenlai County, Jilin Province, China as the research object. The original spectral data were first subjected to Savitzky–Golay (SG) smoothing, multiplicative scattering correction (MSC) pre-processing, and a combined transformation technique. The pre-processed spectral data were then analysed to construct the difference index (DI), ratio index (RI), and normalised difference index (NDI), and the Spearman rank correlation coefficient (r) between these three spectral indices and the salt content in the samples was calculated, while a combined spectral index (r > 0.8) was eventually selected as a sensitive spectral index. Finally, a quantitative inversion model for the salinity of saline soils was developed, and the model’s accuracy was evaluated based on partial least squares regression (PLSR), the random forest (RF) algorithm, and the radial basis function (RBF) neural network algorithm. The results indicated that the inversion of soil salt content using the selected combination of spectral indices based on the RBF neural network algorithm was the most effective, with the prediction model yielding an R2 value of 0.950, a root mean square error (RMSE) of 1.014, and a relative percentage deviation (RPD) of 4.479, which suggested a good prediction effect.

Thermal-Infrared Spectral Feature Analysis and Spectral Identification of Monzonite Using Feature-Oriented Principal Component Analysis

“…Therefore, analysing remote sensing images accurately and quickly by using traditional spectral analysis algorithms is extremely difficult. Considering the potential applications of the TIR spectroscopy of rocks in the fields of land use survey [17,18], lithology mapping [19][20][21] and mineral prospecting [22,23], our team went to the central part of Hunan Province in 2019 to conduct field geological survey and rock sampling. In this paper, the TIR radiation spectra of 19 monzonite samples collected from different regions were measured, and the corresponding features were analysed.…”