Observation and Assessment of Model Retrievals of Surface Exchange Components Over a Row Canopy Using Directional Thermal Data

Land surface temperature is an essential climate variable that can serve as a proxy for detecting water deficiencies in croplands and wooded areas. Its measurement can, however, be influenced by anisotropic properties of surface targets leading to the occurrence of directional effects on the signal. This may lead to an incorrect interpretation of thermal measurements. In this article, we perform model assessments and check the influence of thermal radiation directionality using data over a vineyard. To derive the overall directional surface temperatures, elemental values measured by individual cameras were aggregated according to the respective cover fractions/weights in viewing direction. Aggregated temperatures from the turbid model were compared to corresponding temperatures simulated by the 3-D discrete anisotropic radiative transfer model. The reconstructed temperatures were then used in surface energy balance (SEB) simulations to assess the impact of the sun-target-sensor geometry on retrievals. Here, both the pseudoisotropic Soil Plant Atmosphere Remote Sensing of Evapotranspiration (SPARSE) dual-source model and its nonisotropic version (SPARSE4) were used. Both schemes were able to retrieve overall fluxes satisfactorily, confirming a previous study. However, the sensitivity (of flux and component temperature estimates) of the schemes to viewing direction was tested for the first time using reconstructed sets of directional thermal data to force the models. Degradation (relative to nadir) in flux retrieval cross-row was observed, with better consistency along rows. Overall, it was nevertheless shown that SPARSE4 is less influenced by the viewing direction of the temperature than SPARSE, particularly for strongly off-nadir viewing. Some directional/asymmetrical artifacts are, however, not well reproduced by the simple radiative transfer methods, which can then manifest in and influence the subsequent thermal-infrared-driven SEB modeling.