The accurate estimation of pasture above-ground biomass (AGB) is critical for optimizing stocking rates and ensuring the sustainable use of Mediterranean pastures. This study developed empirical models to estimate fresh (AGBfresh) and dry above-ground biomass (AGBdry) using multispectral imagery acquired by Unmanned Aerial Vehicles (UAVs) in a Hedysarum coronarium pasture in Sicily, Italy. Field biomass was destructively sampled simultaneously with UAV surveys in 28 georeferenced plots during pre- and post-grazing phases over the 2023–2024 and 2024–2025 seasons. Data were collected with a DJI Mavic 3 Multispectral (for the 2024 test) and a DJI Matrice 300 + Altum-PT (for the 2025 test) and radiometrically calibrated to surface reflectance. Because two different multispectral sensors were used across years, an inter-sensor harmonization step was applied before vegetation-index calculation. Thirty-three vegetation indices were extracted as mean values within circular buffers of 1 m radius, centered on each sample plot to accommodate GNSS/georeferencing uncertainty. For each vegetation index, linear and exponential models were calibrated using 66% of the dataset and validated on the remaining 33% to predict fresh and dry above-ground biomass, and model performance was assessed using R2 and RMSE. On the validation dataset, ARVI2 and EVI2 showed the highest explanatory power for AGBfresh (R2 = 0.89), with ARVI2 providing the lower RMSE (2047 g m−2). For AGBdry, visible-band indices such as NGRDI and GRVI were among the best performers, reaching R2 = 0.85 with RMSE = 1371 g m−2. Visible-band greenness indices were among the most competitive predictors, whereas several conventional NIR-based indices showed only moderate performance. Overall, this UAV-based multispectral approach represents a promising and interpretable tool for biomass estimation in heterogeneous Mediterranean pastures, although further validation across additional seasons and sites is required to strengthen its transferability.
Furnitto et al. (Sat,) studied this question.