Integrating 3D radiative transfer and soil spectral models reveals soil–vegetation synergy in arid steppes

In arid and semi-arid regions, the expansion of the shrub-encroached grassland (SEG) has a profound impact on ecosystem dynamics and desertification processes. However, there is a serious lack of research on the interaction between plant community structure and soil using model systems at the scene scale. A repeatable and scalable soil–canopy 3D model framework for arid areas was established, and provided theoretical support and methodological reference for ecological monitoring and desertification control. This study integrated the three-dimensional radiation transfer model (LESS) with the hyperspectral soil reflectance model (GSV) to build a fully parameterized 3D plant–soil fusion simulation framework. Using this framework, we systematically quantified how community structural characteristics and soil background synergistically regulate vegetation community bidirectional reflectance factor (BRF) and normalized difference vegetation index (NDVI). Finally, we validated the simulation results of the fusion model using Sentinel-2 data to evaluate its applicability and accuracy. The simulation results show that the fusion model can accurately reproduce the joint effect of soil reflectance and community structure characteristics on spectral response, especially in the near-infrared (NIR) band with significant differences. The study of community distribution patterns found that the Gap model has the strongest stability and environmental adaptability, while the Spot model can effectively buffer the interference of adverse soil conditions. In addition, the ecological explanatory power and application feasibility of the fusion model were further verified by combining Sentinel-2 NDVI time series data. This study expanded the application boundaries of LESS and GSV models at the community scale. This comprehensive simulation method provides an operational solution for the construction of plant community scenarios in arid areas and related research.