Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/23/2007
Publication Date: 10/1/2007
Citation: Gowda, P., Chavez Eguez, J.L., Colaizzi, P.D., Evett, S.R., Howell, T.A., Tolk, J.A. 2007. Remote sensing based energy balance algorithms for mapping ET: Current status and future challenges. Transactions of the ASABE. 50(5):1639-1644. Interpretive Summary: Reliable regional evapotranspiration (ET) estimates are essential to improve spatial crop water management. Land surface energy balance (EB) models, using remote sensing data from ground to airborne to satellite platforms at different spatial resolutions, have been found to be promising for mapping daily and seasonal ET at both field and regional scales. In this paper, a brief review of numerous remote sensing based models was made to assess the current status of research, underlying principle for each method, data requirements, and their strengths and weaknesses. Although the remote sensing based ET models have been shown to have the potential to accurately estimate regional ET, there are opportunities to further improve these models through (1) developing methods to accurately estimate aerodynamic temperature, (2) testing the spatial validity of the meteorological data such as air temperature and wind speed used in the EB models, and (3) testing the sub-models used to estimate soil heat flux, LAI, crop height, etc., for their accuracy, under various agrometeorological/environmental conditions.
Technical Abstract: Evapotranspiration (ET) is an essential component of the water balance and a major consumptive use of irrigation water and precipitation on crop land. Remote sensing based agrometeorological models are presently most suited for estimating crop water use at both field and regional scales. Numerous ET models have been developed in the last three decades to make use of visible, infrared, and most importantly, thermal data acquired by sensors on airborne and satellite platforms. In this paper, a literature review was done to evaluate numerous remote sensing based algorithms for their ability to accurately estimate regional ET. The remote sensing based models generally have the potential to accurately estimate regional ET; however, there are numerous opportunities to further improve them. The spatial and temporal resolution of currently available remote sensing data from the existing set of earth observing satellite platforms are not sufficient enough to be used in the estimation of spatially distributed ET for on-farm irrigation management purposes, especially at a field scale level (~10-200 ha). This will be constrained further if the thermal sensors on future Landsat satellites are abandoned. Research opportunities exist to improve the spatial and temporal resolution of ET by developing algorithms to increase the spatial resolution of surface temperature data derived from ASTER/MODIS thermal images using same/other-sensor high resolution visible, NIR and SWIR images.