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

Soil Moisture Estimates From AMSR-E Brightness Temperatures by Using a Dual-Frequency Algorithm

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

3 Author(s)
Paloscia, S. ; Inst. of Appl. Phys., Nat. Res. Council (CNR), Florence ; Macelloni, G. ; Santi, E.

This paper investigates the possibility of estimating the soil moisture content (SMC) on a global scale from dual-frequency (C- and X-bands) microwave data of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Because some anomalous behavior was occasionally found in AMSR-E C- and X-band data, a calibration check compared the AMSR-E data with measurements from the SSM/I sensor over two reference targets, namely a Russian evergreen forest and the sea surface, both of which have already been studied in the past. The algorithm for retrieving soil moisture uses both the brightness temperature at C-band in horizontal polarization and the polarization index at X-band for correcting the effects of vegetation. This algorithm is based on a simplified radiative transfer (tau-omega) model, which has been inverted by using the Nelder-Mead iterative minimization method. The algorithm was validated with microwave data collected on two sites during the Microwave Alpine Soil Moisture Experiment 2002 (MASMEx02) and the Soil Moisture Experiment 2002 (SMEX02), respectively. The first site, in Italy, was characterized by natural vegetation covers, whereas the second site, in Iowa (U.S.), was covered primarily in agricultural crops. In general, the soil moisture estimated by the algorithm from AMSR-E data and the SMC measured on the ground were in good agreement with each other in both sites, and five classes of soil moisture were easily identified

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:44 ,  Issue: 11 )

Date of Publication:

Nov. 2006

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.