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

Comparison of Statistical and Multifractal Properties of Soil Moisture and Brightness Temperature From ESTAR and PSR During SGP99

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)
Mascaro, G. ; Dipt. di Ing. del Territorio, Univ. of Cagliari, Cagliari, Italy ; Vivoni, E.R.

Global soil moisture products are based on passive microwave sensors of brightness temperature at different frequencies, including Land C-bands. Two airborne sensors used to develop and test retrieval algorithms for soil moisture estimation are the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) and the C-band Polarimetric Scanning Radiometer (PSR). In this letter, we compare the statistical and multifractal properties of soil moisture and brightness temperature from ESTAR and PSR during the Southern Great Plains Experiment in 1999. We show that differences between products are minimized at a support scale close to the satellite resolution. Then, we compare the subfootprint variabilities of each product in eight coarse domains of 25.6 × 25.6 km2. Scale-invariance and multifractal properties were found in all the three available soil moisture products, but multifractality was negligible in brightness temperature fields, implying that the nonlinear transformations in retrieval algorithms introduce the multifractal behavior in soil moisture. Subfootprint variability and the multifractal behavior for diverse wetness conditions are also different for the three products. Since discrepancies between the subfootprint variabilities of PSR and ESTAR brightness temperatures are small, the factors leading to the differences among the soil moisture products are mainly due to the level of detail of the retrieval algorithm and to the spatial variability of forcing data and parameters related to surface roughness and vegetation.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:9 ,  Issue: 3 )

Date of Publication:

May 2012

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.