A tool for quantifying Grapevines Vigour: Accurate canopy cover and crop volume assessment via drone-based point clouds from conventional and oblique RGB cameras

This study aimed to develop a tool capable of capturing the spatial variability of grapevine vigour from a geometric approach. The methodology was evaluated during the 2023, 2024, and 2025 growing seasons in a 1.27 ha trellised vineyard in Tarazona de la Mancha (Albacete, Spain). Green canopy cover (GCC) estimates were compared with reference data obtained using GEO-LAIC software across 33 uncrewed aerial vehicle (UAV) flights. Biomass volume (BV) estimates were compared with values derived from the alphashape algorithm using 10540 observations. The relationship between BV and pruning weight was also assessed to identify the optimal period for biomass estimation. GCC estimates showed strong agreement with GEO-LAIC, achieving coefficients of determination (R 2 ) of up to 0.97 and root mean square error (RMSE) values below 0.04. BV estimates showed moderate agreement with the alphashape-derived values (R 2 = 0.65), providing a basis for further calibration. The optimal period for estimating pruning weight was identified between BBCH growth stages 75 and 81. BV showed a stronger relationship with pruning weight than GCC. The proposed geometric approach effectively captures grapevine vigour variability while prioritising geometric accuracy over radiometric quality, potentially enabling the use of low-cost RGB sensors. This methodology offers a promising tool for precision viticulture and spatially targeted vineyard management.