This contribute presents a water stress detection investigation in maize canopies using hyperspectral remote sensing (RS) imagery. An airborne survey using AISA (Specim, Finland) hyperspectral sensor was performed in July 2008 over an experimental farm in Italy. Hyperspectral data were acquired over a maize field with three different irrigation regimes to study the spatial variability of crop variables as a function of water stress. An intensive field campaign was also conducted concurrently with AISA acquisition to measure crop variables such as: leaf water content, active chlorophyll fluorescence, plant structure and LAI measurements. Preliminary results show that RS data allow the estimation of crop variables affected by water stress. This study demonstrates the potential applicability of RS data in precision agriculture for optimizing irrigation management.