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Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Mapping Daily Evapotranspiration at Field to Global Scales using Geostationary and Polar Orbiting Satellite Imagery

Authors
item Anderson, Martha
item Kustas, William
item Norman, John -
item Hain, Christopher -
item Mecikalski, John -
item Schultz, Lori -
item Gonzalez-Dugo, Maria -
item Cammalleri, Carmello -
item D'Urso, Guido -
item Pimstein, Agustin -

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: August 16, 2010
Publication Date: September 15, 2010
Citation: Anderson, M.C., Kustas, W.P., Norman, J., Hain, C., Mecikalski, J., Schultz, L., Gonzalez-Dugo, M.P., Cammalleri, C., D'Urso, G., Pimstein, A. 2010. Mapping daily evapotranspiration at field to global scales using geostationary and polar orbiting satellite imagery [abstract]. Surface analysis SAF-2010 User Workshop. 2010 CDROM.

Technical Abstract: Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) 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 (soil moisture, 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. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5-10 km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI), spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach will be presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions of 30 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the U.S. Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites . Work is underway to further evaluate multi-scale ALEXI implementations over the U.S., Europe and, Africa and other continents with geostationary satellite coverage.

   

 
Project Team
Crow, Wade
Cosh, Michael
Kustas, William - Bill
Alfieri, Joseph
McCarty, Gregory
Sadeghi, Ali
Gish, Timothy
Jackson, Thomas
Anderson, Martha
 
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