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Title:   Author  item
                                            Kustas, William

                                                         - *Bill*item
                                            Anderson, Marthaitem
                                            MECIKALSKI, JOHN - University Of Alabamaitem
                                            HAIN, CHRISTOPHER - University Of Alabama
  Submitted to: Meeting Abstract
                                    Publication Type: Proceedings
                                    Publication Acceptance Date: 1/17/2010
                                    Publication  Date: 2/18/2010
                                    Citation: Kustas, W.P., Anderson, M.C., Mecikalski, J.R., Hain, C.R. 2010. Using thermal remote sensing for drought and evapotranspiration monitoring. In: Proceedings of the Earth Observation and Water Cycle, November 18-20, 2009, Frascati, Italy. 2010 CDROM.Interpretive Summary:
                                Technical Abstract: Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status for estimating evapotranspiration and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (radiation, advection, air temperature) are affecting plant stress. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. This approach, the Atmosphere-Land Exchange Inverse (ALEXI) model, couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). The ALEXI model has potential for global applications by integrating data from other geostationary meteorological satellite systems, such as the European METEOSAT and the Chinese FY-2B. Work is underway to further evaluate multi-scale ALEXI implementations over the U.S. and other continents with geostationary satellite coverage.


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