Estimation of Crop Evapotranspiration from High Resolution Thermal Imagery

Latent heat flux is directly related to evapotranspiration (ET). The TSEB (Two-Source Energy Balance) model was developed for satellite remote sensing to estimate surface latent and sensible heat flux from coarse resolution pixels that represent fields or mixtures of fields. With the emergence of unmanned aerial system (UAS) remote sensing, this model needs to be adapted to be applied to the significantly higher resolution imagery. We acquire thermal infrared imagery from a UAS platform with an average resolution of about 7 cm, which means multiple temperature measurements are obtained for a single plant and for the soil in between plants. An adaptative thresholding algorithm is applied to classify pixels into 2 categories: soil and plant. Then the adapted model is used for estimating latent and sensible heat flux of soil and plants at the pixel level. Outputs from the model are evaluated versus stomatal conductance measurements from a steady state porometer, as well as local potential evaporation measurements. Results indicate a high correlation relationship (R²> 0.85) exists between estimated and reference latent heat flux. It is also found that best latent heat estimates are achieved during cloudless weather conditions when solar radiation does not change abruptly. Findings from this research provide a relatively easy and accurate way to estimate instant crop ET for people who want insights into crop water usage and can be further used as a tool for crop genotypic selection for high water use efficiency and drought tolerance.