The use of remote sensors (thermometers and cameras) to analyse crop water status in field conditions is fraught with several difficulties. In particular, average canopy temperature measurements are affected by the mixture of soil and green regions, the mutual shading of leaves and the variability of absorbed radiation. The aim of the study was to analyse how the selection of different 'regions of interest' (ROI) in canopy images affect the variability of the resulting temperature averages. Using automated image segmentation techniques we computed the average temperature in four nested ROI of decreasing size, from the whole image down to the sunlit fraction of a leaf located in the upper part of the canopy. The study was conducted on maize (Zea mays L.) at the flowering stage, for its large leaves and well structured canopy. Our results suggest that, under these conditions, the ROI comprising the sunlit fraction of a leaf located in the upper part of the canopy should be analogous to the single leaf approach (in controlled conditions) that allows the estimation of stomatal conductance or plant water potential.