By Topic

Soil Moisture Estimation Using High-Resolution Spotlight TerraSAR-X Data

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
$33 $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)
Matej Kseneman ; Faculty of Electrical Engineering and Computer Science, Signal Processing and Remote Sensing, University of Maribor, Maribor, Slovenia ; Dušan Gleich ; Žarko Cucej

High-resolution and dual polarized Spotlight TerraSAR-X images are assessed for soil moisture parameter retrieval. This letter presents bare soil moisture estimation and estimation of moisture of vegetated areas. The bare soil moisture estimation is based on the Shi model. The Minimum Mean Square Error approach is used to determine the unknown parameters of the Shi model using ground measurements of volumetric moisture and SAR data. The soil moisture of vegetated areas is estimated using the vegetation and soil backscattering coefficients. The unknown parameters of vegetation and soil backscattering models were estimated using Tikhonov optimization. The experimental results showed that the used models provide good results for estimating bare soil moisture and moisture of vegetated areas.

Published in:

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