Knowledge on the spatiotemporal patterns of surface energy balance parameters is crucial for understanding climate system processes. To this end, the assimilation of Earth Observation data with land biosphere models has shown promising results, but they are still hampered by several limitations related to the spatiotemporal resolution of EO sensors and cloud contamination. With the recent developments on Unmanned Aerial Vehicles (UAVs), there is a great opportunity to overcome these challenges and gain knowledge of surface energy balance parameters at unprecedented resolutions. The present study examines, for the first time, the ability of an inversion-modeling scheme, the so-called “analytical triangle” method, to retrieve estimates of surface energy fluxes and soil surface moisture (SSM) at high spatial resolution using UAV data. A further aim of our study was to examine the representativeness of the SSM estimates for the SM measurements taken at different depths. The selected experimental site is an agricultural site of citrus trees located near the city of Palermo on 30 July 2019. The results of comparisons showed that the sensible and latent heat fluxes from UAV were consistent with those measured from the ground, with absolute differences in comparison to ground measurements being 5.00 Wm−2 for the latent heat (LE) flux and 65.02 Wm−2 for H flux, whereas for the daytime fluxes H/Rn and LE/Rn were 0.161 and 0.012, respectively. When comparing analytical triangle SSM estimates with SM measurements made at different depths, it was found that there was a gradual increase in underestimation with increasing measurement depth. All in all, this study’s results provide a credible demonstration of the significant potential of the technique investigated herein as a cost-effective and rapid solution for estimating key parameters characterizing land surface processes. As those parameters are required by a wide range of disciplines and applications, utilization of the investigated technique in research and practical applications is expected to be seen in the future.