Next Article in Journal
Modeling Glacier Elevation Change from DEM Time Series
Previous Article in Journal
Application of Multispectral Sensors Carried on Unmanned Aerial Vehicle (UAV) to Trophic State Mapping of Small Reservoirs: A Case Study of Tain-Pu Reservoir in Kinmen, Taiwan
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(8), 10098-10116; doi:10.3390/rs70810098

Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images

1
CESBIO (CNRS/UPS/IRD/CNES), 18 av. Edouard Belin, 31401 Toulouse cedex 9, France
2
Rural engineering, water and forest department, INAT/University of Carthage, 43, Avenue Charles Nicolle 1082 Tunis-Mahrajène, Tunisia
3
IRSTEA, UMR TETIS, 500 rue François Breton, 34093 Montpellier cedex 5, France
*
Authors to whom correspondence should be addressed.
Academic Editors: Wolfgang Wagner and Prasad S. Thenkabail
Received: 19 May 2015 / Revised: 30 June 2015 / Accepted: 28 July 2015 / Published: 7 August 2015
View Full-Text   |   Download PDF [1249 KB, uploaded 7 August 2015]   |  

Abstract

The aim of this paper is to propose a methodology combing multi-temporal X-band SAR images (TerraSAR-X) with continuous ground thetaprobe measurements, for the retrieval of surface soil moisture and texture at a high spatial resolution. Our analysis is based on seven radar images acquired at a 36° incidence angle in the HH polarization, over a semi-arid site in Tunisia (North Africa). The soil moisture estimations are based on an empirical change detection approach using TerraSAR-X data and ground auxiliary thetaprobe network measurements. Two assumptions were tested: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. By considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved. Maps of soil moisture, clay and sand percentages at the studied site are derived. View Full-Text
Keywords: TerraSAR-X; radar; soil moisture; texture; clay content soil moisture; soil roughness TerraSAR-X; radar; soil moisture; texture; clay content soil moisture; soil roughness
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Gorrab, A.; Zribi, M.; Baghdadi, N.; Mougenot, B.; Fanise, P.; Chabaane, Z.L. Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images. Remote Sens. 2015, 7, 10098-10116.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top