Spatiotemporal Variation in Understory Litter Coverage Based on Multi-Angle Remote Sensing Inversion Using Sentinel-2 and MODIS BRDF Imagery

The forest understory litter fraction (FVCy) is a critical indicator for evaluating the effectiveness of “understory erosion” control in red soil regions; however, its high-precision, large-scale monitoring remains challenging due to canopy occlusion. This study proposes an FVCy inversion framework that integrates high-spatial-resolution Sentinel-2 imagery with multi-angular prior knowledge from MODIS BRDF products. First, a linear mapping model between multi-band reflectances at 0° and 45° view angles was constructed using 500 m MODIS MCD43A1 products (R2>0.8). This model was subsequently employed as a physical prior for anisotropic characterization and transferred to 10 m Sentinel-2 imagery to generate a long-term, dual-angle reflectance dataset. Subsequently, the four-scale geometric-optical model was utilized to decouple canopy and understory background signals, followed by quantitative FVCy inversion using a pixel-based dimidiate model. Validation results confirmed the reliability of the framework (R2=0.74, RMSE=0.1073). Spatiotemporal evolution analysis indicated a significant upward trend in FVCy across Changting County from 2016 to 2025, with over 90% of the area showing improvement. The proportion of high-coverage areas (FVCy>0.75) increased from 10% to 38%, exhibiting a “high in the center, low in the periphery” spatial pattern that aligns closely with core ecological restoration zones. Stability and persistence analyses further revealed that 61.18% of the study area reached moderate-to-high stability, and 70% of pixels exhibited a “positive persistence-improvement” trend, highlighting a pronounced inertia-driven enhancement in ecological recovery. This study provides a refined technical pathway for assessing soil and water conservation benefits in red soil regions.