From Retrieval to Fate: UAV-Based Hyperspectral Remote Sensing of Soil Nitrogen and Its Leaching Risks in a Wheat-Maize Rotation System

Spatiotemporally continuous monitoring of soil nitrogen is essential for rational farmland nitrogen management and non-point source pollution control. This study focused on a typical wheat-maize rotation system in the North China Plain under four nitrogen fertilizer application levels (N0: 0 kg/ha; N200: 200 kg/ha; N400: 400 kg/ha; N600: 600 kg/ha). By integrating soil profile sampling with UAV-based hyperspectral remote sensing, we identified soil nitrogen distribution characteristics and established a retrieval relationship between hyperspectral data and seasonal soil nitrogen dynamics. Results showed that higher nitrogen fertilizer levels significantly increased soil nitrogen content, with N400 and N600 causing nitrate nitrogen (NO3−-N) peaks in both surface and deep layers indicating leaching risk. Hyperspectral imagery at the jointing stage, combined with PLSR and XGBoost-SHAP models, effectively retrieved NO3−-N at 0–50 cm depths. Canopy spectral traits correlated with nitrogen leaching and deep accumulation, suggesting they can serve as early indicators of leaching risk. The “sky-ground” collaborative approach provides conceptual and technical support for precise nitrogen management and pollution control.