HR: 1330h
AN: H22D-0952    [PDF]
TI: Remote Sensing Spatial Resolution Analysis Using a Two-Source Energy Balance Model for SMEX02/SMACEX
AU: * Li, F
EM: fcl@hydrolab.arsusda.gov
AF: USDA ARS Hydrology and Remote Sensing Lab, Room 104, Bldg 007, BARC-West, Beltsville, MD 20705 United States
AU: Kustas, W P
EM: bkustas@hydrolab.arsusda.gov
AF: USDA ARS Hydrology and Remote Sensing Lab, Room 104, Bldg 007, BARC-West, Beltsville, MD 20705 United States
AU: Jackson, T J
EM: tjackson@hydrolab.arsusda.gov
AF: USDA ARS Hydrology and Remote Sensing Lab, Room 104, Bldg 007, BARC-West, Beltsville, MD 20705 United States
AB: As part of the Soil Moisture Atmosphere Coupling Experiment (SMACEX) conducted during the Soil Moisture Experiment 2002 (SMEX02) in June and July, the potential impact of spatial resolution of input data derived by remote sensing on flux estimation was analyzed. Land surface temperature and the Normalized Difference Water Index (NDWI) derived from remotely sensed data along with meteorological data were used as provide inputs for a two-source canopy model. This model evaluates soil and vegetation contributions to the energy fluxes and radiometric surface temperature. The primary source of remotely sensed data was the Landsat satellites. The model and the Landsat data were used to estimate land surface fluxes over the watershed area. These high resolution estimates clearly showed spatial and temporal variations due to the different crop covers (primarily corn and soybean) and management practices. In particular, surface temperature showed very significant spatial variation at the Landsat pixel resolution. These spatial variations are difficult to observe in a coarse resolution image, such as MODIS or AVHRR and it is clear that a great deal of spatial information that is useful at the field scale is lost when AVHRR or MODIS is used. As validation, the fluxes estimated from the two-source model were compared with those derived from aircraft based flux data. Although there are differences the simple two-source model provides a useful technique to use with remotely sensed thermal and NIR/SWIR data. Spatial variations in the fluxes at different spatial scales were also analyzed to investigate the impact of resolution on radiative properties and resulting impact on energy and water flux estimation.
DE: 1800 HYDROLOGY
DE: 1818 Evapotranspiration
DE: 1833 Hydroclimatology
DE: 1866 Soil moisture
DE: 1878 Water/energy interactions
SC: Hydrology [H]
MN: 2003 Fall Meeting