By Topic

Influence of near-surface soil moisture on regional scale heat fluxes: model results using microwave remote sensing data from SGP97

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Bindlish, R. ; USDA-ARS Hydrology Lab., Beltsville, MD, USA ; Kustas, W.P. ; French, A.N. ; Diak, G.R.
more authors

During the 1997 Southern Great Plains Hydrology Experiment (SGP97), passive microwave observations using the L-band electronically scanned thinned array radiometer (ESTAR) were used to extend surface soil moisture retrieval algorithms to coarser resolutions and larger regions with more diverse conditions. This near-surface soil moisture product (W) at 800 m pixel resolution together with land use and fractional vegetation cover (fc) estimated from normalized difference vegetation index (NDVI) was used for computing spatially distributed sensible (H) and latent (LE) heat fluxes over the SGP97 domain (an area ~40×260 km) using a remote sensing model (called the two-source energy Balance-soil moisture, TSEBSM, model). With regional maps of W and the heat fluxes, spatial correlations were computed to evaluate the influence of W on H and LE. For the whole SGP97 domain and full range in fc, correlations (R) between W and LE varied from 0.4 to 0.6 (R~0.5 on average), while correlations between W and H varied from -0.3 to -0.7 (R~-0.6 on average). The W-LE and W-H correlations were dramatically higher when variability due to fc was considered by using NDVI as a surrogate for fc and computing R between heat fluxes and corresponding W values under similar fractional vegetation cover conditions. The results showed a steady decline in correlation with increasing NDVI or fc. Typically, |R|≳0.9 for data sorted by NDVI having values ≲0.5 or fc ≲0.5, while |R|≲0.5 for the data sorted under high canopy cover where NDVI≳0.6 or fc≳0.7

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:39 ,  Issue: 8 )