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Title:   Author  item
                                            AGAM, NURIT - VISITING SCIENTISTitem
                                            Kustas, William

                                                         - *Bill*item
                                            Anderson, Marthaitem
                                            Li, Fuqinitem
                                            Colaizzi, Paul
  Submitted to: Geophysical Research Letters
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 3/3/2008
                                    Publication  Date: 4/7/2008
                                    Citation: Agam, N., Kustas, W.P., Anderson, M.C., Li, F., Colaizzi, P.D. 2008. Utility of thermal image sharpening for monitoring field-scale evapotranspiration over rainfed and irrigated agricultural regions. Geophysical Research Letters. 35, L02402, http://dx.doi.org/10.1029/2007GL032195.Interpretive Summary: Over the last several decades, there has been a major effort to develop surface energy balance models for deriving spatially-distributed evapotranspiration (ET) maps over landscapes by using remote sensing imagery in the visible–near-infrared (VIS/NIR) providing vegetation indices, which relate to fractional canopy cover, and the thermal infrared (TIR) bands for estimating land surface temperature (LST).  For water management applications and other agricultural purposes, ET maps would be optimally produced daily at high/fine spatial resolution (< 100 m).  However, a trade-off exists between the spatial and temporal resolutions of current remote sensing systems, such that they typically have either high-spatial/low-temporal or low-spatial/high-temporal resolution.  For daily coverage of a region,  the Moderate Resolution Imaging Spectrometer (MODIS) on board the Terra/Aqua satellites is available. A strategy that utilizes the functional relationship between the spaceborne-derived land surface temperature and vegetation indices to sharpen 1-km MODIS TIR imagery to the resolution of the MODIS VIS/NIR bands (250m), deriving near daily ET maps at scales marginally resolving the typical field size is proposed. A Two-Source (soil + vegetation)-Model (TSM) of surface energy balance was used to derive field-scale resolution ET maps using TIR data at different spatial resolutions. The utility of TsHARP for TSM flux evaluations was examined over two agricultural regions in the U.S.: a rainfed corn and soybean production region in the Walnut Creek watershed in central Iowa, and an irrigated agricultural area in the Texas High Plains within the Texas Panhandle. It is concluded that in the absence of fine (sub-field scale) resolution thermal data, TsHARP provides an important tool for routine monitoring ET over rainfed agricultural areas with satellite observations.  In contrast, over irrigated regions, TsHARP applied to kilometer-resolution TIR imagery is unable to provide accurate fine resolution LST due to significant sub-pixel moisture variations that are not captured in the sharpening procedure.  Consequently, reliable estimation of ET and crop stress requires thermal imagery acquired at high spatial resolution, resolving the dominant length-scales of moisture variability present within the landscape.
                                Technical Abstract: The utility of a thermal image sharpening algorithm (TsHARP) in providing fine resolution land surface temperature (LST) data to a Two-Source-Model (TSM) for mapping evapotranspiration (ET) was examined over two agricultural regions in the U.S.  One site is in a rainfed corn and soybean production region in central Iowa.  The other lies within the Texas High Plains, an irrigated agricultural area.  It is concluded that in the absence of fine (sub-field scale) resolution thermal data, TsHARP provides an important tool for monitoring ET over rainfed agricultural areas.  In contrast, over irrigated regions, TsHARP applied to kilometer-resolution thermal imagery is unable to provide accurate fine resolution LST due to significant sub-pixel moisture variations that are not captured in the sharpening procedure.  Consequently, reliable estimation of ET and crop stress requires thermal imagery acquired at high spatial resolution, resolving the dominant length-scales of moisture variability present within the landscape.


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