Quantifying the Relationship Between the FPAR and Vegetation Index in Marsh Wetlands Using a 3D Radiative Transfer Model and Satellite Observations

Wetland ecosystems, particularly marsh wetlands, are vital for carbon cycling, yet the accurate estimation of the fraction of absorbed photosynthetically active radiation (FPAR) in these environments is challenging due to their complex structure and limited field data. This study employs the large-scale remote sensing data and image simulation framework (LESS), a 3D radiative transfer model, to simulate FPAR and vegetation indices (VIs) under controlled conditions, including variations in vegetation types, soil types, chlorophyll content, solar and observation angles, and plant density. By simulating 8064 wetland scenes, we overcame the limitations of field measurements and conducted comprehensive quantitative analyses of the relationship between the FPAR and VI (which is essential for remote sensing-based FPAR estimation). Nine VIs (NDVI, GNDVI, SAVI, RVI, EVI, MTCI, DVI, kNDVI, RDVI) effectively characterized FPAR, with the following saturation thresholds quantified: inflection points (FPAR.inf, where saturation begins) ranged from 0.423 to 0.762 (mean = 0.594) and critical saturation points (FPAR.sat, where saturation is complete) from 0.654 to 0.889 (mean = 0.817). The Enhanced Vegetation Index (EVI) and Soil-Adjusted Vegetation Index (SAVI) showed the highest robustness against saturation and environmental variability for FPAR estimation in reed (Phragmites australis) marshes. These findings provide essential support for FPAR estimation in marsh wetlands and contribute to quantitative studies of wetland carbon cycling.