UAV-Based Spectral and Thermal Indices in Precision Viticulture: A Review of NDVI, NDRE, SAVI, GNDVI, and CWSI
Adrián Vera-Esmeraldas, Sebastián Pizarro‐Oteíza, Mariela Labbé, Francisco Rojo, Fernando Salazar
Abstract
Unmanned aerial vehicles (UAVs) with multispectral sensors are transforming precision viticulture by enabling detailed monitoring of vineyard variability. Vegetation indices such as NDVI, NDRE, GNDVI, and SAVI are widely applied to estimate vine vigor, canopy structure, and water status. Beyond agronomic traits, UAV-derived indices can inform grape composition, including sugar content (°Brix), total phenolics, anthocyanins, titratable acidity, berry weight, and yield variables measurable in the field or laboratory to validate spectral predictions. Strengths of UAV approaches include high spatial resolution, rapid data acquisition, and flexibility across vineyard blocks, while limitations involve index saturation in dense canopies (e.g., Merlot, Cabernet Sauvignon), environmental sensitivity, and calibration requirements across varieties and phenological cycles. Integrating UAV data with ground-based measurements (leaf sampling, yield mapping, proximal or thermal sensors) improves model accuracy and stress detection. Abiotic stresses (water deficit, nutrient deficiency) can be distinguished from biotic factors (pest and fungal infections), supporting timely interventions. Compared to manned aircraft or satellite platforms, UAVs offer cost-effective, high-resolution imagery for precision vineyard management. Future directions include combining UAV indices with machine learning and data fusion to predict grape maturity and wine quality, enhancing decision-making in sustainable viticulture and precision enology.