Next Article in Journal
Application of a Remote Sensing Method for Estimating Monthly Blue Water Evapotranspiration in Irrigated Agriculture
Previous Article in Journal
Now You See It… Now You Don’t: Understanding Airborne Mapping LiDAR Collection and Data Product Generation for Archaeological Research in Mesoamerica
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2014, 6(10), 10002-10032; doi:10.3390/rs61010002

Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data

1
IRSTEA, UMR TETIS, 500 rue François Breton, 34093 Montpellier cedex 5, France
2
SupAgro, UMR G-EAU, 2 place Pierre Viala, 34060 Montpellier, France
3
CESBIO, UMR 5126 CNES, CNRS, Université de Toulouse, IRD, 18 av. Edouard Belin, bpi 2801, 31401 Toulouse cedex 9, France
4
IRSTEA, UMR G-EAU, 361 rue François Breton, 34196 Montpellier cedex 5, France
5
INRA, UMR 1114 EMMAH, Domaine St. Paul, 84914, Avignon, France
*
Author to whom correspondence should be addressed.
Received: 16 June 2014 / Revised: 25 September 2014 / Accepted: 13 October 2014 / Published: 20 October 2014
View Full-Text   |   Download PDF [6480 KB, uploaded 23 October 2014]   |  

Abstract

The objective of this study was to analyze the sensitivity of radar signals in the X-band in irrigated grassland conditions. The backscattered radar signals were analyzed according to soil moisture and vegetation parameters using linear regression models. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT and LANDSAT) images was acquired at a high temporal frequency in 2013 over a small agricultural region in southeastern France. Ground measurements were conducted simultaneously with the satellite data acquisitions during several grassland growing cycles to monitor the evolution of the soil and vegetation characteristics. The comparison between the Normalized Difference Vegetation Index (NDVI) computed from optical images and the in situ Leaf Area Index (LAI) showed a logarithmic relationship with a greater scattering for the dates corresponding to vegetation well developed before the harvest. The correlation between the NDVI and the vegetation parameters (LAI, vegetation height, biomass, and vegetation water content) was high at the beginning of the growth cycle. This correlation became insensitive at a certain threshold corresponding to high vegetation (LAI ~2.5 m2/m2). Results showed that the radar signal depends on variations in soil moisture, with a higher sensitivity to soil moisture for biomass lower than 1 kg/m². HH and HV polarizations had approximately similar sensitivities to soil moisture. The penetration depth of the radar wave in the X-band was high, even for dense and high vegetation; flooded areas were visible in the images with higher detection potential in HH polarization than in HV polarization, even for vegetation heights reaching 1 m. Lower sensitivity was observed at the X-band between the radar signal and the vegetation parameters with very limited potential of the X-band to monitor grassland growth. These results showed that it is possible to track gravity irrigation and soil moisture variations from SAR X-band images acquired at high spatial resolution (an incidence angle near 30°). View Full-Text
Keywords: grassland; irrigation; TerraSAR-X; COSMO-SkyMed; SPOT-4; LANDSAT; soil moisture; vegetation parameters grassland; irrigation; TerraSAR-X; COSMO-SkyMed; SPOT-4; LANDSAT; soil moisture; vegetation parameters
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

Hajj, M.E.; Baghdadi, N.; Belaud, G.; Zribi, M.; Cheviron, B.; Courault, D.; Hagolle, O.; Charron, F. Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data. Remote Sens. 2014, 6, 10002-10032.

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