Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 2/24/2005
Publication Date: 5/23/2005
Citation: Li, F., Kustas, W.P., Jackson, T.J., Bindlish, R., Prueger, J.H. 2005. Estimating land surface fluxes using microwave and thermal remote sensing data during SMEX02/SMACEX [abstract]. EOS Transactions, American Geophysical Union, Joint Assembly Supplement. 86(18), Paper No. H23B-01.
Technical Abstract: A two-source (soil + vegetation) energy balance model using microwave-derived near-surface soil moisture (TSM sm) as input was applied to a corn and soybean production region in central Iowa. Six days of the Polarimetric Scanning Radiometer (PSR) derived soil moisture data and Landsat derived vegetation information as well as local meteorological data were used to run the model. These data were acquired during the Soil Moisture Experiment in 2002 (SMEX02) and the Soil Moisture Atmosphere Coupling Experiment (SMACEX). The PSR derived soil moisture maps at 800 m resolution which were resampled to 30 m. At this higher resolution, a flux footprint model was applied to weight pixels within the source area of the flux tower measurements. The root mean square difference (RMSD) values between TSM sm model also produced reasonable estimates of sensible heat (H) and latent heat flux (LE) with both RMSD values for H and LE being within 55 W m -2. The TSM sm model output was also compared with estimates from the two-source model version using radiometric surface temperature observations (TSM th) from Landsat. The results from two Landsat overpasses under partial canopy cover on July 1, 2002, and near full cover on July 8. When the two models were in good agreement, the surface temperature estimated from TSM sm agreed closely with the Landsat radiometric temperature observations. By contrast, when TSM sm output gave greater differences with TSM th flux estimates and tower measurements such as July 8, the TSM sm model generally computed lower LE and higher H than TSM th and the tower measurements.