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Proceedings Paper

Integration and weighting of remotely sensed energy balance fluxes
Author(s): Christopher M. U. Neale; Jose L. Chavez; Raghuveer Vinukollu
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Paper Abstract

Many studies in the past have used remote sensing techniques to estimate evapotranspiration from cropped and naturally vegetated surfaces. These studies have reported differences between estimated values and ground measured evapotranspiration rates using a variety of methods such as Bowen ratio and eddy covariance flux systems. The mixed results of this body of research could be due to the fact that remotely sensed latent heat fluxes generally were integrated using simple arithmetic averages of pixel values, around the reference flux stations. Recently, techniques have been developed1 to properly weight and integrate remotely sensed distributed heat fluxes according to the contributing areas upwind from ground-based flux stations. This paper describes the application of a 2-D source area (footprint) function for the integration of remotely sensed latent and sensible heat fluxes estimated from short-wave and thermal high-resolution airborne multispectral digital imagery as well as Landsat Thematic Mapper imagery. Comparisons are made against heat fluxes measured over corn and soybean fields using thirteen eddy covariance flux towers. The data were collected over a period of three weeks during the summer of 2002 close to Ames, Iowa as part of the SMACEX/SMEX02 experiment funded by NASA. The rain fed corn and soybean crops were in their vegetative stage of growth during the period, presenting considerable surface heterogeneity in plant cover and leaf area. Results show that remotely sensed fluxes integrated using the footprint functions compared well to the ground measured fluxes and that the methodology was valid for satellite-based fluxes.

Paper Details

Date Published: 18 October 2005
PDF: 12 pages
Proc. SPIE 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, 59760M (18 October 2005); doi: 10.1117/12.631070
Show Author Affiliations
Christopher M. U. Neale, Utah State Univ. (United States)
Jose L. Chavez, Washington State Univ. (United States)
Raghuveer Vinukollu, Utah State Univ. (United States)

Published in SPIE Proceedings Vol. 5976:
Remote Sensing for Agriculture, Ecosystems, and Hydrology VII
Manfred Owe; Guido D'Urso, Editor(s)

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