Remote sensing algorithms are currently being used to estimate regional surface fluxes (e.g. evapotranspiration (ET)). Many of these surface energy balance models use information derived from satellite imagery such as aircraft, Landsat, AVHRR, ASTER, and MODIS to estimate ET. The remote sensing approach to estimating ET provides advantages over traditional methods. One of the most important advantages is that it can provide estimates of actual ET for each pixel in the image. Most conventional methods are based on point measurements, limiting their ability to capture the spatial variability of ET. Another advantage of remote sensing/surface energy balance ET models is that they are able to estimate the actual crop ET as a residual of the energy balance without the need of using reference crop ET and crop coefficients. This presentation will focus on the use of an energy balance model developed by the authors (Remote Sensing of ET – ReSET) that uses an enhanced procedure to deal with the spatial and temporal variability of ET. ET estimates from several years of data for fields in the Arkansas River Basin, South Platte and Palo Verde Irrigation District will be presented. The presentation will focus on how remote sensing of ET can be used to quantify the spatial variability of ET inside a field and identify problem areas inside a field. This technology can also be used to determine the amount of water used by plants inside a field which could be the basis for determining how much water to apply in order to meet the crop water demand for each area in a field.