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United States Department of Agriculture

Agricultural Research Service

Title: Evaluating the Effects of Sub-Pixel Heterogeneity on Pixel Average Fluxes

Authors
item KUSTAS, WILLIAM
item Norman, John - UNIVERSITY OF WISCONSIN

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 17, 1999
Publication Date: January 13, 2000

Interpretive Summary: The spatial distribution in evapotranspiration (ET) across a watershed is critical in gaining an understanding of the interaction between terrestrial ecosystems and climate. Remote sensing data can provide spatially distributed information on a number of key land surface characteristics and state variables which control ET. By combining weather satellite data, which are routinely available, with meteorological data and a relatively simple model, spatial "maps" of ET can be produced operationally. The pixel resolution of satellite data dictates the resolution of the model output and hence, will invariably result in errors in pixel-averaged ET estimation for surfaces with significant variability in vegetation cover and stress conditions. Uncertainty in ET due to significant sub-pixel heterogeneity is examined using the simplified two-source model for a wide range of contrasting cover types and conditions. Significant errors in pixel-average ET are found in many cases. Additionally, the results are influenced by the wind conditions with higher wind speeds tending to reduce errors. This preliminary analysis suggests that when there is a significant discontinuity in vegetation cover under light winds, the sub-pixel variability in ET will likely cause significant errors in model predictions, particularly when using course resolution data. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument proposed for NASA's Earth Observing System (EOS) has 90 m resolution. ASTER data combined with this modeling approach will be useful for evaluating the impact of sub-pixel variability on flux predictions obtained from coarser resolution satellite data.

Technical Abstract: Directional radiometric temperature observations are routinely available from weather satellites and provide a unique spatially distributed boundary condition for surface energy balance modeling at regional scales. A simple two-source energy balance model developed to use radiometric temperature observations has been applied successfully to a wide range of vegetation cover conditions. However, its application with course resolution weather satellite data will invariably result in errors in pixel-averaged heat flux estimation for surfaces with significant variability in vegetation cover and stress conditions. Uncertainty in flux estimation due to significant sub-pixel heterogeneity is examined using the simplified two-source model with radiometric temperature inputs from plant-environmental model simulations under four different contrasting cover types and conditions Significant errors in pixel-average heat fluxes are found in many cases. Additionally, the results are influenced by the wind conditions with highe wind speeds tending to reduce errors. This preliminary analysis suggests that when there is a significant discontinuity in vegetation cover under light winds, the sub-pixel variability in energy fluxes will likely cause significant errors in two-source model predictions, particularly when using course resolution satellite-based observations. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument proposed for NASA's Earth Observing System (EOS) has 90 m resolution. This will be useful for evaluating the impact of sub-pixel variability on flux predictions with coarser resolution data more routinely available from weather satellites.

Last Modified: 7/28/2014
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