Estimating maize water stress by standard deviation of canopy temperature in thermal imagery

Abstract

A new crop water stress indicator, standard deviation of canopy temperature within a thermal image (CTSD), was developed to monitor crop water status. In this study, thermal imagery was taken from maize (Zea mays L.) under various levels of deficit irrigation at different crop growing stages. The Expectation-Maximization algorithm was used to estimate the canopy temperature distribution from thermal imagery under a range of crop coverage and water stress conditions. Soil water deficit (SWD), leaf water potential (ψ), stomatal conductance, and other crop water stress indices were used to evaluate the CTSD. We found that the temperature differences between sunlit and shaded parts of the canopy would increase with larger canopy resistance in the sunlit part of the crop canopy. The CTSD well described impact of irrigation events (timing and depth) on crop water stress. All water stress measurements showed statistically significant relationship with CTSD. Although CTSD is not sensitive to small changes in water stress, the result suggests that the canopy temperature standard deviation could be used as a water stress indicator. This index has strong application potential because it only relies on the canopy temperature itself, and is easy to calculate. Moreover, it may also be applied to high resolution thermal imagery from other remote sensing platforms, such as unmanned aerial vehicles.