Modis and Landsat ETM+ scaling study on the daily evapotranspiration over heterogeneous landscapes

Abstract

Routine (i.e., daily to weekly) monitoring of surface energy fluxes, particularly evapotranspiration (ET), using satellite observations of radiometric surface temperature has not been feasible at high pixel resolution because of the low frequency in satellite coverage over the region of interest (i.e., approximately every 2 weeks). Cloud cover further reduces the number of useable observations of surface conditions resulting in high-resolution satellite imagery of a region typically being available once a month, which is not very useful for routine ET monitoring. Radiometric surface temperature observations at more than 1 km pixel resolution are available multiple times per day from several satellites. However, this spatial resolution is too coarse for estimating ET from individual agricultural fields or for defining variations in ET due to land cover changes. In this paper, Landsat ETM+ data in the visible and near-infrared wavelengths, are used for computing vegetation indices provide higher resolution information(60 m resolution) on vegetation cover conditions. Then the vegetation index-radiometric surface temperature relationship is exploited and utilized in a disaggregation procedure for estimating subpixel variation in surface temperature. In addition, a remote sensing-based energy balance model is used to compare output using Landsat ETM+ data versus estimated surface temperatures. From these comparisons, the utility of the surface temperature disaggregation technique appears to be most useful for estimating subpixel surface temperatures at resolutions corresponding to length scales defining agricultural field boundaries across the landscape. Finally, the simplified model to estimate daily ET is revised considering the scaling effect on heterogeneous region.