Evapotranspiration (ET) estimation in desert-oasis ecotones remains challenging due to sparse meteorological observations and the coarse spatial resolution of satellite remote sensing, which limit the ability to resolve highly heterogeneous surface conditions. To address this issue, this study develops a high-resolution ET estimation framework by integrating unmanned aerial vehicle (UAV)-based thermal infrared remote sensing with a three-temperature (3T) model in the Hexi Corridor. UAV-derived land surface temperature (LST) at meter-scale resolution, together with meteorological and vegetation data, was used to drive the model and generate high-resolution ET maps. The model’s performance was validated spatially against the Surface Energy Balance Algorithm for Land (SEBAL) model and at the point-scale against a two-source model. The results show that: (1) The 3T model effectively captured the spatial gradient of decreasing ET from cropland (3–10.69 mm d−1), through shelterbelts (3–6 mm d−1), to desert areas (<3 mm d−1). (2) Spatial validation against the SEBAL model was conducted using stratified pixel-wise comparisons across four land-cover types over 14 UAV transects, showing strong agreement (R2 = 0.90–0.95; RMSE = 0.22–0.43 mm d−1). The model achieved highest accuracy in cropland (R2 = 0.92; RMSE = 0.24 mm d−1), with slight overestimation in shelterbelts. (3) Point-scale validation against the two-source model yielded an MAE of 0.38 mm d−1. This study demonstrates the effectiveness of combining UAV thermal infrared data with the 3T model for high-resolution ET simulation in complex ecological transition zones, offering a promising technical approach for ecohydrological monitoring and water resource assessment in arid regions.
Li et al. (Tue,) studied this question.
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