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This article in AJ

  1. Vol. 99 No. 1, p. 240-254
    Received: Apr 1, 2005

    * Corresponding author(s): manderson@hydrolab.arsusda.gov
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Upscaling Flux Observations from Local to Continental Scales Using Thermal Remote Sensing

  1. Martha C. Anderson *a,
  2. William P. Kustasa and
  3. John M. Normanb
  1. a USDA-ARS, Hydrology and Remote Sensing Lab., Bldg. 007, BARC West, 10300 Baltimore Ave., Beltsville, MD 20705
    b Dep. of Soil Science, Univ. of Wisconsin, Madison, WI 53706


A number of recent intensive and extended field campaigns have been devoted to the collection of land-surface fluxes from a variety of platforms, with the purpose of inferring the long-term C, water, and energy budgets across large areas (watershed, continental, or global scales). One approach to flux upscaling is to use land–atmosphere transfer schemes (LATS) linked to remotely sensed boundary conditions as an intermediary between the sensor footprint and regional scales. In this capacity, we examined the utility of a multiscale LATS framework that uses thermal, visible and near infrared remote sensing imagery from multiple satellites to partition surface temperature and fluxes between the soil and canopy. We conducted exercises using tower and aircraft flux data collected at three experiment sites in Oklahoma and Iowa, each with a different configuration of instrumentation. Combined, the two flux-monitoring systems were found to be complementary: the towers provided high-spatial-resolution, time-continuous validation at discrete points within the modeling domain, while with the aircraft data it could be confirmed that the model was reproducing broad spatial patterns observed at specific moments in time. High-resolution flux maps created with the LATS allowed evaluation of differences in footprint associated with turbulent, radiative, and conductive flux sensors, which may be contributing to energy budget closure problems observed with eddy correlation systems. The ability to map fluxes at multiple resolutions (1 m–10 km) with a common model framework is beneficial in providing spatial context to an experiment by bracketing the scale of interest. Multiscale flux maps can also assist in the experimental design stage, in a priori assessments of sensor representativeness in complex landscapes.

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