A novel strategy for improving canopy nitrogen density retrieval by deciphering saturation effects and vertical heterogeneity

Abstract

Canopy nitrogen density (CND) is a critical indicator of plant growth, with applications in nutrient diagnosis, disease monitoring, and carbon cycling. However, optical remote sensing of nitrogen is constrained by VI saturation, particularly in dense canopies. Here, we propose a novel strategy to mitigate saturation by resolving two key issues: (1) the sensing depth of canopy spectra and (2) the quantification of vertical nitrogen heterogeneity. Saturation characteristics of VIs were first analyzed using inflection and saturation points. We found that CND at the inflection point enhanced the linear correlation with canopy spectra. The 3rd–7th leaf layers contributed most to canopy reflectance, accounting for 67.24%–72.15% of canopy spectra and 62.39% of total CND. Beyond the 7th–8th leaf layers, saturation became prominent. To capture vertical heterogeneity, we employed a bell-shaped model, with the coefficient ω linking the inflection point CND to canopy CND across structural variations. Integrating inflection points with vertical heterogeneity characteristics improved the robustness of VI–CND relationships, reducing RMSE by 10.8%–33.9%. This approach offers an intuitive framework to mitigate VI saturation, enabling more accurate CND estimation under diverse field conditions.

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