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Title: ESTIMATING SUBPIXEL SURFACE TEMPERATURES AND ENERGY FLUXES FROM THE VEGETATION INDEX-RADIOMETRIC TEMPERATURE RELATIONSHIP

Author
item Kustas, William - Bill
item ANDERSON, MARTHA - UNIVERSITY OF WISCONSIN
item NORMAN, JOHN - UNIVERSITY OF WISCONSIN
item FRENCH, ANDREWN - NASA/GSFC

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/15/2002
Publication Date: 7/10/2003
Citation: KUSTAS, W.P., ANDERSON, M., NORMAN, J., FRENCH, A.N. ESTIMATING SUBPIXEL SURFACE TEMPERATURES AND ENERGY FLUXES FROM THE VEGETATION INDEX-RADIOMETRIC TEMPERATURE RELATIONSHIP. REMOTE SENSING OF ENVIRONMENT. 2003.

Interpretive Summary: Routine (i.e., daily to weekly) monitoring of evapotranspiration (ET) using satellite observations of land surface temperature has not been feasible at high pixel resolution because of the low frequency in satellite coverage over the region of interest. Cloud cover further reduces the number of useable observations of surface conditions resulting in high resolution satellite imagery typically being available only once a month. Coarse resolution satellite observations of land surface temperature are available multiple times per day from several weather satellites, but the spatial resolution is not appropriate for estimating ET from individual agricultural fields. However some of these satellites collect remotely sensed data used for computing vegetation indices, which are at pixel resolutions enabling an assessment of vegetation cover conditions of individual fields. A number of studies have exploited the relationship between vegetation indices and land surface temperature for estimating ET model parameters. In this study, the vegetation index-radiometric surface temperature relationship is utilized in a disaggregation procedure for estimating sub-pixel variation in surface temperature with imagery collected over the U.S. Southern Great Plains. The disaggregated land surface temperatures estimated by this procedure are compared to actual observations at this sub-pixel resolution. In addition, a remote sensing-based ET model is used to compare output using actual versus estimated land surface temperatures over a range of pixel resolutions. From these comparisons, the utility of the land surface temperature disaggregation technique appears to be most useful for estimating sub-pixel surface temperatures at resolutions corresponding to length scales defining agricultural field boundaries across the landscape. This technique will be instrumental in achieving more routine ET monitoring of individual agricultural fields using satellite remote sensing.

Technical 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 ~1 to 5 km pixel resolution are available multiple times per day from several weather 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. Satellite data in the visible and near-infrared wavelengths, used for computing vegetation indices, are available at resolutions an order of magnitude smaller than in the thermal-infrared, and hence provide higher resolution information on vegetation cover conditions. A number of studies have exploited the relationship between vegetation indices and radiometric surface temperature for estimating model parameters used in computing spatially distributed fluxes and available moisture. In this paper, the vegetation index-radiometric surface temperature relationship is utilized in a disaggregation procedure for estimating subpixel variation in surface temperature with aircraft imagery collected over the U.S. Southern Great Plains. The disaggregated surface temperatures estimated by this procedure are compared to actual observations at this subpixel resolution. In addition, a remote sensing-based energy balance model is used to compare output using actual versus estimated surface temperatures over a range of pixel resolutions. 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.