Remote Sensing Based Energy Balance Algorithms for Mapping ET: Current Status and Future Challenges

Abstract

Evapotranspiration (ET) is an essential component of the water balance and a major consumptive use of irrigation water and precipitation on cropland. Remote sensing based agrometeorological models are presently most suited for estimating crop water use at both field and regional scales. Numerous ET models have been developed in the last three decades to make use of visible, near-infrared (NIR), shortwave infrared (SWIR), and most importantly, thermal data acquired by sensors on airborne and satellite platforms. In this article, a literature review is done to evaluate numerous remote sensing based algorithms for their ability to accurately estimate regional ET. The remote sensing based models generally have the potential to accurately estimate regional ET; however, there are numerous opportunities to further improve them. The spatial and temporal resolution of currently available remote sensing data from the existing set of earth-observing satellite platforms are not sufficient enough to be used in the estimation of spatially distributed ET for on-farm irrigation scheduling purposes, especially at the field scale (~10 to 200 ha). This will be constrained further if the thermal sensors on future Landsat satellites are abandoned. Research opportunities exist to improve the spatial and temporal resolution of ET by developing algorithms to increase the spatial resolution of surface temperature data derived from ASTER/MODIS thermal images using same/other-sensor high-resolution visible, NIR, and SWIR images.