The estimation of combined water loss from soil evaporation and plant transpiration using satellite-based thermal and vegetation data. Remote sensing enables spatially distributed ET estimates over large areas where ground measurements are impractical.
Evapotranspiration (ET) estimated via remote sensing uses satellite observations of land surface temperature, vegetation indices, and albedo to calculate the energy balance at the Earth's surface. The most widely used approaches include SEBAL (Surface Energy Balance Algorithm for Land), METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration), and the MODIS ET product (MOD16). These methods solve the surface energy balance equation: Rn = G + H + LE, where Rn is net radiation, G is soil heat flux, H is sensible heat flux, and LE is latent heat flux (the energy used for ET). Thermal infrared bands from Landsat and MODIS are critical inputs because land surface temperature is a direct indicator of evaporative cooling. Remote sensing ET estimates are vital for irrigation management, drought monitoring, water rights enforcement, and hydrological water balance studies. OpenET, a collaborative platform, now provides field-scale ET data across the western United States using an ensemble of six satellite-based models. Validation against eddy covariance flux towers shows that ensemble ET estimates typically achieve accuracies within 10-20% at monthly timescales.