A Triangle-Based Method for Downscaling Land Surface Evapotranspiration

Remote sensing-based evapotranspiration (ET) has been widely used in the study of global climate change, water resources management and precision agriculture. However, due to the relative coarser spatial resolution of thermal infrared data obtained by remote sensing, the retrievals of fine resolution ET through different remote sensing-based models were full of challenge. In this paper, a general ET downscaling method based on the land surface temperature-vegetation index (T
s
-VI) triangle was proposed. 990 m resolution ET datasets obtained by aggregating 90 m surface energy balance algorithm for land (SEBAL)-derived estimates from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over a spatial dimension of 9.9 km by 9.9 km around the AmeriFlux US-Ne1 site were downscaled to 90 m by using this new proposed T
s
-VI-based ET downscaling method. Compared with the original 90 m ASTER ET, the 90 m downscaled ET results had a mean absolute error (MAE) of 19.2~40.2 W/m
²
, a root mean square error (RMSE) of 28.8~52.0 W/m
²
and a bias of 1.7~2.4 W/m
²
.