|Kustas, William - Bill|
Submitted to: Remote Sensing of Environment
Publication Type: Peer reviewed journal
Publication Acceptance Date: 5/14/2005
Publication Date: 11/15/2005
Citation: French, A.N., Jacob, F., Anderson, M.C., Kustas, W.P., Timmermans, W., Gieske, A., Su, B., Su, H., McCabe, M.F., Li, F., Prueger, J.H., Brunsell, N. 2005. Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA). Remote Sensing of Environment. 99:55-65. Corrigendum 99:471. Interpretive Summary: Crop growth and crop yields frequently show large spatial variations within and between fields, despite uniform farm management. One reason for these variations is the inequality of plant water use caused by spatial changes in landscape and environmental conditions. In order to optimize use of scarce resources such as irrigation water, spatial quantification of plant evapotranspiration (ET) is essential. Currently, however, most ET estimates have no spatial representation. The only potentially practical way to monitor ET spatial variations at farm scales is to use high resolution remote sensing observations of land surfaces. This potential is demonstrated using a satellite-based sensor known as ASTER, a remote sensing package available nowhere else. Observations at 15 to 90 meter scales retrieve surface temperatures and vegetation densities which are used to create ET maps in two different ways over croplands. When verified, the methods used to build these ET maps could greatly help farmers manage their croplands through more effective irrigation scheduling at local scales and could also help water policy decision makers plan and allocate seasonal use of irrigation water at regional scales.
Technical Abstract: Accurate estimation of surface energy fluxes from space at high spatial resolution would significantly improve modeling the impact of land use changes on the local environment and provide a means to assess local crop conditions. To achieve this goal, a combination of physically-based models using high quality remote sensing data are needed. Data from the ASTER sensor are particularly suited to the task, as it collects high spatial resolution (15 -90 m), imagery in visible, near-infrared, and thermal infrared bands. Data in these bands reveal surface temperature, vegetation cover density, and land use types, all critical inputs to surface energy balance models for assessing local environmental conditions. ASTER is currently the only satellite sensor collecting multispectral thermal infrared imagery, a capability allowing unprecedented surface temperature estimation accuracy for a variety of surface cover types. Surface energy flux retrieval from ASTER is demonstrated using data collected over an experimental site in central Iowa, in the framework of the Soil Moisture Atmosphere Coupling Experiment (SMACEX). This experiment took place during the summer 2002 study over heterogeneous agricultural croplands. Two different flux estimation approaches, designed to account for the spatial variability, are considered: the Two Source Energy Balance model (TSEB) and the Surface Energy Balance Algorithm for Land model (SEBAL). ASTER data are shown to have sufficient spatial and spectral resolution to derive surface variables required as inputs for physically-based energy balance modeling. Comparison of flux models against each other and against ground based measurements was promising, with flux values commonly agreeing within approximately 50 W m -2 of each other. Both TSEB and SEBAL showed systematic agreement and responded to spatially varying surface temperatures and vegetation densities. Direct comparison against ground Eddy Covariance data suggests that the TSEB approach is helpful over sparsely vegetated terrain. Availability of ASTER data to study surface energy fluxes allows direct comparisons against ground measurements and facilitates detection of modeling limitations, both possible because of ASTER's higher spatial resolution.