Estimation of crop water stress in a nectarine orchard using high-resolution imagery from unmanned aerial vehicle (UAV)

Abstract

Adequate and timely irrigation based on real-time monitoring of crop water status is critical for efficient and sustainable water use. However, detection of water status in large crop fields is not a trivial task as manual inspection can be time consuming and costly. Moreover, the symptoms of water stress are visually detectable only after the crops are already in a significantly water deficient stage. Consequently, capability of monitoring water status in crops on a regular basis could maximize productivity and water use efficiency. As an indicator, the crop water stress index (CWSI) has been widely used to estimate water status in the crop fields. CWSI can be derived from ground-based leaf..