Dr. Mehrez Zribi Profile

Dr. Mehrez Zribi

at Ctr d'Etudes Spatiales de la Biosphère

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Publications (6)

Proceedings Article | 12 September 2021 Presentation + Paper

ALOS-2 and Sentinel-1 use for retrieving soil moisture over cereal fields in semi-arid area: the Kairouan plain – central Tunisia

Emna Ayari, Zeineb Kassouk, Zohra Lili-Chabaane, Nicolas Baghdadi, Safa Bousbih, Mehrez Zribi

Proceedings Volume 11856, 1185612 (2021) https://doi.org/10.1117/12.2599730

KEYWORDS: Soil science, Vegetation, Radar, Data modeling, L band, Synthetic aperture radar, Polarization, Backscatter, Calibration, Signal attenuation

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Proceedings Article | 12 September 2021 Presentation + Paper

Analysis of agronomic drought context based on satellite remote sensing over Western Mediterranean region

M. Zribi, S. Nativel, M. Le Page

Proceedings Volume 11856, 1185611 (2021) https://doi.org/10.1117/12.2599402

KEYWORDS: Vegetation, Agriculture, Soil science, Satellites, Remote sensing, MODIS, Climatology, Radar

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Proceedings Article | 12 September 2021 Presentation + Paper

Root-zone soil moisture from process-based and remote sensing features in ANN

Roiya Souissi, Mehrez Zribi, Ahmad Al Bitar

Proceedings Volume 11856, 1185613 (2021) https://doi.org/10.1117/12.2599867

KEYWORDS: Soil science, Remote sensing, Artificial neural networks

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Proceedings Article | 14 October 2015 Paper

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

A. Gorrab, M. Zribi, N. Baghdadi, Z. Lili Chabaane

Proceedings Volume 9637, 96371F (2015) https://doi.org/10.1117/12.2194947

KEYWORDS: Soil science, Radar, Backscatter, X band, Synthetic aperture radar, Statistical analysis, Polarization, Spatial resolution, Surface roughness, Sensors

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The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (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.

Finally, 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.

Proceedings Article | 14 October 2015 Paper

Forecasting of cereals yields in a semi-arid area using the agrometeorological model «SAFY» combined to optical SPOT/HRV images

Aicha Chahbi, Mehrez Zribi, Zohra Lili-Chabaane, Bernard Mougenot

Proceedings Volume 9637, 963729 (2015) https://doi.org/10.1117/12.2194913

KEYWORDS: Vegetation, Satellites, Calibration, Agriculture, Remote sensing, Data modeling, Satellite imaging, Algorithm development, Data acquisition, Biological research

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Proceedings Article | 14 October 2015 Paper

GLORI: a new airborne GNSS reflectometry instrument for land surface monitoring

Erwan Motte, Pascal Fanise, Mehrez Zribi

Proceedings Volume 9637, 963715 (2015) https://doi.org/10.1117/12.2192686

KEYWORDS: Satellite navigation systems, Reflectivity, Soil science, Reflectometry, Receivers, Global Positioning System, Scattering, Satellites, L band, Biological research

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Showing 5 of 6 publications

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