The close dependence of surface temperature on actual evapotranspiration makes
thermal remote sensing suitable for crop consumptive use studies. Jackson et al. (1977)
performed pioneering work on thermal infrared applications for a wheat mono-cropping
system. Several new methods have been developed afterwards and a review on
evapotranspiration algorithms using remotely sensed data is given by Kustas and Norman
(1996). Among the newest models is the Surface Energy Balance Algorithm for Land
(SEBAL) for heterogeneous terrain. SEBAL describes the spatial variability of most
micro-meteorological variables with semi-empirical functions. SEBAL can be applied for
diverse agro-ecosystems and does not require ancillary information on land use or crop
types (Bastiaanssen et al., 1998). The validation efforts have shown that the error at a 1 ha
scale varies between 10 and 20% and that the uncertainty diminishes with increasing
scale. For an area of 1000 ha, the error is reduced to 5% and for regions of 1 million ha of
farmland, the error becomes negligibly small.