A first assessment of airborne HyTES-based land surface temperature and evapotranspiration

Abstract

The Hyperspectral Thermal Emission Spectrometer (HyTES) offers high spatial and spectral resolution thermal infrared (TIR) airborne measurements, which are crucial for deriving land surface temperature and emissivity (LST&E). These measurements have wide-ranging applications, particularly in understanding water stress and plant water use. One critical application of TIR satellite-sensor systems is the estimation of evapotranspiration (ET), which can be derived from LST. ET is essential for modeling water fluxes from the land surface, and various algorithms leverage LST as a key boundary condition for this purpose. In this study, we apply an ET algorithm to HyTES LST data for the first time, using an analytical surface energy balance model, the Surface Temperature Initiated Closure (STIC) version 1.3. We provide an overview of the STIC model, detailing its application to HyTES data, including the integration of ancillary datasets. We demonstrate the practicality of this approach by presenting ET and LST calculations for HyTES flightlines from three field campaigns conducted in 2019, 2021, and 2023. To validate our results, we compare the derived ET and LST against available in situ measurements, including eddy covariance-derived latent heat flux and radiometer-derived LST. While this study focuses on HyTES data, the same methodology is applicable to any instantaneous LST dataset. Advancing TIR mapping of ET is crucial for applications in agriculture, water management and for understanding the evolving water cycle.