Research on Ground-Based Remote-Sensing Inversion Method for Soil Salinity Information Based on Crack Characteristics and Spectral Response

Abstract

The precise quantification of soil salinity and the spatial distribution are paramount for proficiently managing and remediating salinized soils. This study aims to explore a pioneering methodology for forecasting soil salinity by combining the spectroscopy of soda saline–alkali soil with crack characteristics, thereby facilitating the ground-based remote-sensing inversion of soil salinity. To attain this objective, a surface cracking experiment was meticulously conducted under controlled indoor conditions for 57 soda saline–alkali soil samples from the Songnen Plain of China. The quantitative parameters for crack characterization, encompassing the length and area of desiccation cracks, together with the contrast texture feature were methodically derived. Furthermore, spectral reflectance of the cracked soil surface was measured. A structural equation model (SEM) was then employed for the estimation of soil salt parameters, including electrical conductivity (EC1:5), Na+, pH, HCO3−, CO32−, and the total salinity. The investigation unveiled notable associations between different salt parameters and crack attributes, alongside spectral reflectance measurements (r = 0.52–0.95), yet both clay content and mineralogy had little effect on the cracking process due to its low activity index. In addition, the presence of desiccation cracks accentuated the overall spectral contrast of salt-affected soil samples. The application of SEMs facilitated the concurrent prediction of multiple soil salt parameters alongside the regression analysis for individual salt parameters. Nonetheless, this study confers the advantage of the swift synchronous observation of multiple salt parameters whilst furnishing lucid interpretation and pragmatic utility. This study helps us to explore the mechanism of soil salinity on the surface cracking of soda saline–alkali soil in the Songnen Plain of China, and it also provides an effective solution for quickly and accurately predicting soil salt content using crack characteristics, which also provides a new perspective for the hyperspectral measurement of saline–alkali soils.