Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
ISSN-L : 0026-1165
Articles
Evaluation of Empirical Remote Sensing-Based Equations for Estimating Soil Heat Flux
Zhigang SUN, Mekonnen GEBREMICHAEL, Qinxue WANG
Author information
  • Zhigang SUN

    Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan

  • Mekonnen GEBREMICHAEL

    Civil & Environmental Engineering, University of Connecticut, CT, USA

  • Qinxue WANG

    Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan

Corresponding author

ORCID
Keywords: soil heat flux, vegetation index, albedo, land surface temperature, soil moisture, MODIS
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Supplementary material

2013 Volume 91 Issue 5 Pages 627-638

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  • Published: 2013 Received: July 30, 2012 Released on J-STAGE: November 29, 2013 Accepted: June 05, 2013 Advance online publication: - Revised: -
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Abstract
 Accurate estimation of evapotranspiration from remotely sensed data typically requires accurate estimation of net radiation, sensible heat flux, and soil heat flux (G). The focus of this paper is on evaluating the accuracy of commonly used empirical soil-heat-flux-estimating equations. The equations were applied to estimate the ratio (Γ) of G to net radiation using 250-m resolution Moderate Resolution Imaging Spectroradiometer (or MODIS) vegetation index data from the Terra and Aqua satellites and ground measurements at three sites in China that represent humid, semi-arid, and arid climates.
 The results revealed the following: equations that determine Γ on the basis of the vegetation index alone give highly inaccurate results; information on soil moisture condition is critical to obtain more reliable Γ estimates; soil moisture condition of bare soil is related to its albedo in a log-linear way. A new equation has been developed that considers the effect of soil moisture condition through the albedo of bare soil; this equation has been shown to produce highly accurate results over a wide range of climate and land cover types. It is expected that the proposed G-estimating equation could be embedded in remote sensing evapotranspiration algorithms in future studies.
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