RESUMEN
An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements.
RESUMEN
An extension to the two-step physical retrieval algorithm was developed. Combined clear-sky multitemporal and multispectral observations were used to retrieve the atmospheric temperature-humidity profile, land-surface temperature, and surface emissivities in the midwave (3-5 microns) and long-wave (8-14.5 microns) regions. The extended algorithm was tested with both simulated and real data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator. A sensitivity study and error analysis demonstrate that retrieval performance is improved by the extended algorithm. The extended algorithm is relatively insensitive to the uncertainties simulated for the real observations. The extended algorithm was also applied to real MODIS daytime and nighttime observations and showed that it is capable of retrieving medium-scale atmospheric temperature water vapor and retrieving surface temperature emissivity with retrieval accuracy similar to that achieved by the Geostationary Operational Environmental Satellite (GOES) but at a spatial resolution higher than that of GOES.