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Title: Potential Errors in the Application of Thermal-Based Energy Balance Models with Coarse Resolution Data

Author
item AGAM, NURIT - VISITING SCIENTIST
item Kustas, William - Bill
item Anderson, Martha
item Li, Fuqin

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 3/24/2007
Publication Date: 4/25/2007
Citation: Agam, N., Kustas, W.P., Anderson, M.C. Li, F. 2007. Potential errors in the application of thermal-based energy balance models with course resolution data [abstract]. Abs. 01. BARC Poster Day.

Interpretive Summary:

Technical Abstract: A thermal infrared (TIR)-based two-source (soil + vegetation) energy balance (TSEB) model, validated with remotely sensed imagery over a wide variety of landscapes, is applied to to the Texas High Plains region characterized by significant variability in vegetation cover and soil moisture conditions. The TSEB model uses sub-field TIR pixel data (60 m) from Landsat ETM aggregated to 120 m, 240 m and ~1 km resolution to assess potential model errors and inability to discriminate fluxes from individual fields with the coarser resolution data. The motivation for this study stems from the fact that there are no definitive plans for supporting any future satellite-based high resolution (~100 m) TIR sensor, specifically on the next proposed Landsat platform. Therefore, in the near future only km-scale TIR data will be available from satellite sensors (e.g., MODIS). A methodology for sharpening TIR data from coarser resolutions as a means of obtaining higher resolution thermal imagery was applied to the 1-km imagery and compared to the native resolution data. The resulting errors in fluxes between native versus sharpened TIR used by the TSEB model were analyzed as well as differences in aggregated fluxes applying the TSEB model with coarse versus high resolution TIR data. It is concluded that having no Earth observing TIR satellite system with resolutions similar to Landsat for modeling surface fluxes, water use and crop/vegetation stress for distinct land cover types is essential. Furthermore, errors in regional-scale estimates and on validation using flux tower observations were assessed.