Thermal imaging is a potential tool for estimating plant temperature, which can be used as an indicator of stomatal closure and water deficit stress. In this study, a new method for processing and analysing thermal images was developed. By using remote sensing software, the information from thermal and visible images was combined, the images were classified to identify leaf area and sunlit and shaded parts of the canopy, and the temperature statistics for specific canopy components were calculated. The method was applied to data from a greenhouse water-stress experiment of Vicia faba L. and to field data for Vitis vinifera L. Vaseline-covered and water-sprayed plants were used as dry and wet references, respectively, and two thermal indices, based on temperature differences between the canopy and reference surfaces, were calculated for single Vicia faba plants. The thermal indices were compared with measured stomatal conductance. The temperature distributions of sunlit and shaded leaf area of Vitis vinifera canopies from natural rainfall and irrigation treatments were compared. The present method provides two major improvements compared with earlier methods for calculating thermal indices. First, it allows more accurate estimation of the indices, which are consequently more closely related to stomatal conductance. Second, it gives more accurate estimates of the temperature distribution of the shaded and sunlit parts of canopy, and, unlike the earlier methods, makes it possible to quantify the relationship between temperature variation and stomatal conductance.