TY  - EJOUR
AU  - Strati, Virginia 
AU  - Albéri, Matteo 
AU  - Barbagli, Alessio 
AU  - Boncompagni, Stefano 
AU  - Casoli, Luca 
AU  - Chiarelli, Enrico 
AU  - Colla, Ruggero 
AU  - Colonna, Tommaso 
AU  - Elek, Nedime I. 
AU  - Galli, Gabriele 
AU  - Gallorini, Fabio 
AU  - Guastaldi, Enrico 
AU  - Hasnain, Ghulam 
AU  - Lopane, Nicola 
AU  - Maino, Andrea 
AU  - Mantovani, Fabio 
AU  - Mantovani, Filippo 
AU  - Mazzoli, Gian L. 
AU  - Migliorini, Federica 
AU  - Petrone, Dario 
AU  - Pierini, Silvio 
AU  - Raptis, Kassandra G. 
AU  - Tiso, Rocchina 
TI  - Advancing Grapevine Disease Detection Through Airborne Imaging: A Pilot Study in Emilia-Romagna (Italy)
T2  - Remote Sensing
PY  - 2025
VL  - 17
IS  - 14
SN  - 2072-4292
AB  - Innovative applications of high-resolution airborne imaging are explored for detecting grapevine diseases. Driven by the motivation to enhance early disease detection, the method’s effectiveness lies in its capacity to identify isolated cases of grapevine yellows (Flavescence dorée and Bois Noir) and trunk disease (Esca complex), crucial for preventing the disease from spreading to unaffected areas. Conducted over a 17 ha vineyard in the Forlì municipality in Emilia-Romagna (Italy), the aerial survey utilized a photogrammetric camera capturing centimeter-level resolution images of the whole area in 17 minutes. These images were then processed through an automated analysis leveraging RGB-based spectral indices (Green–Red Vegetation Index—GRVI, Green–Blue Vegetation Index—GBVI, and Blue–Red Vegetation Index—BRVI). The analysis scanned the 1.24 · 109 pixels of the orthomosaic, detecting 0.4% of the vineyard area showing evidence of disease. The instances, density, and incidence maps provide insights into symptoms’ spatial distribution and facilitate precise interventions. High specificity (0.96) and good sensitivity (0.56) emerged from the ground field observation campaign. Statistical analysis revealed a significant edge effect in symptom distribution, with higher disease occurrence near vineyard borders. This pattern, confirmed by spatial autocorrelation and non-parametric tests, likely reflects increased vector activity and environmental stress at the vineyard margins. The presented pilot study not only provides a reliable detection tool for grapevine diseases but also lays the groundwork for an early warning system that, if extended to larger areas, could offer a valuable system to guide on-the-ground monitoring and facilitate strategic decision-making by the authorities.
KW  - Flavescence dorée
KW  - Esca complex
KW  - Bois Noir
KW  - vegetation indices
KW  - GRVI
DO  - 10.3390/rs17142465
ER  -