Inversion of heavy metal elements in characteristic agricultural areas of Shanxi Province: Application of the airborne multimodular imaging spectrometer

Abstract

The heavy metal content in soil is a key factor affecting farmland ecosystems, and high-precision aerial remote sensing is an effective tool for monitoring soil contamination. In this study, the Airborne Multimodular Imaging Spectrometer was used to collect data, which are combined with field soil samples, were analyzed to assess the spectral characteristics of Zn, Fe, and Cu. The original bands are combined into band groups, followed by band selection through the successive projections algorithm and optimum index factor. A random forest model was applied to predict metal concentrations, and model accuracy was verified. The results show that higher metal concentrations correspond to greater spectral reflectance. Spatial distribution analysis revealed that high Zn concentrations were found in the northwestern and south-central ravine areas, while low concentrations were in the southwestern and north-central regions. Fe and Cu had higher concentrations in the northwest and lower concentrations in the central and southern areas. The inversion model showed high accuracy, with R² values of 0.918, 0.934, and 0.917 for Zn, Fe, and Cu, respectively. Overall, the contents of the three elements were low, with recommendations to supplement Fe and Cu in areas growing Scutellaria baicalensis and Rehmannia glutinosa to maintain the quality of specialty crops.