10. Precision monitoring of vine water stress using UAVs and opensource processing chains

Abstract

This work aimed to evaluate the potential of visible-near-infrared (VNIR) and thermal infrared (TIR) imagery, acquired from an unmanned aerial vehicle (UAV), to detect vine water status. Three irrigation treatments were designed to impose weekly evapotranspiration (ET) to K C = 0.2, K C = 0.4 and K C = 0.8 of reference ET. In-situ leaf area index (LAI) and midday leaf (Ψ Leaf ) and stem water potential were collected during seven UAV overpasses. TIR-based temperature correlated highly with the water status variability observed between treatments (Ψ Leaf : r = -0.68). However, VNIR indices were less correlated with Ψ Leaf (r < 0.4), revealing the importance of TIR imaging to capture the vine physiological response to water stress, with foliage differences being less apparent between treatments.