Cart (Loading....) | Create Account
Close category search window
 

On the Retrieval of Soil Moisture in Wheat Fields From L-Band SAR Based on Water Cloud Modeling, the IEM, and Effective Roughness Parameters

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

2 Author(s)
Lievens, H. ; Lab. of Hydrol. & Water Manage., Ghent Univ., Ghent, Belgium ; Verhoest, N.E.C.

The synthetic aperture radar (SAR)-based soil moisture retrieval of agricultural fields is often hampered by vegetation effects on the backscattered signal. The semiempirical water cloud model (WCM) allows for estimating the backscatter of a vegetated surface, accounting for both the contributions of the vegetation and the underlying soil. The latter is often described through the integral equation model (IEM). Unfortunately, the IEM requires an accurate parameterization of the surface roughness which is very difficult to achieve. Therefore, this letter extends the WCM with a bare soil contribution that is based on the IEM, which, however, relies on calibrated or effective roughness parameters. Furthermore, this letter compares a number of vegetation indicators for their use in the WCM. Based on a series of L-band SAR observations, it is shown that effective roughness parameters are a promising tool for soil moisture retrieval under a wheat canopy and that the use of a leaf area index may be recommended above other vegetation indicators, as it leads to the lowest root-mean-square errors of about 5.5 vol%. These results prove the operational potential of L-band SAR data for soil moisture inferred under a wheat canopy throughout the entire crop growth cycle.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:8 ,  Issue: 4 )

Date of Publication:

July 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.