Using remote sensing to quantify the temporal and spatial effects of extreme weather events in vineyards

Introduction ‐ The increasing frequency of extreme weather events (EWE) represents a severe threat to viticulture. The accurate and early assessment of plant stress condition offers substantial advantages to minimize the effects of EWE. Vegetation indices obtained by remote sensing could provide useful information for early detection and quantification of abiotic stresses.
Methods ‐ The analysis assessed several vineyards in Italy and Australia recently affected by EWE (2016‐ 18). The spatio‐temporal pattern of EWE (heatwaves, late frost) and their effects on vineyards were assessed by analysing the evolution of specific vegetation indices calculated using satellite imagery. The magnitude of indices variations was used to quantify the extent of canopy damage. Temporal variations were used to calculate the time necessary for complete recovery of the plants.
Results ‐ Different spectral bands (NIR, red edge, SWIR, green and red) and several vegetation indices provided information to quantify the extension of the areas damaged by EWE. The comparison of the indices values and single bands in affected and unaffected areas allowed the estimation of the temporal pattern in different climate conditions of the studied areas. Specifically, it was possible to quantify the recovery time, needed by plants to return to an acceptable vigour after damages induced by frost. The results provided a basis for better understanding and management of EWE effects.
Discussion ‐ The implementation of remote sensing techniques is widely used to monitor water status and spatial variability of the vineyards. By contrast, there is less application of these tools for monitoring effects and damages due to EWE. The results of this study demonstrate that the analysis of vegetation indices computed from remote sensing imagery can provide factual information of the spatio‐temporal pattern of vineyards affected by EWE. The methodology established could be used to support decision‐ making towards calamity alleviation, insurance services and recovery management.

Authors: Alessia COGATO1, Massimiliano DE ANTONI MIGLIORATI2, Vinay PAGAY3, Francesco MARINELLO1, Franco MEGGIO4, Peter GRACE2 

(1) University of Padova, TESAF, Viale dell’Università 16, 35020 Padova, Italy 
(2)Queensland University of Technology QUT,2 George St, Brisbane City QLD 4000, Australia 
(3)The University of Adelaide, Adelaide, South Australia 5005, Australia 
(4) University of Padova, DAFNAE, Viale dell’Università 16, 35020 Padova, Italy 


Keywords: Grapevine,Extreme weather events, Climate change, Remote sensing, Spatio‐temporal pattern

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