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Wheat Water Deficit Monitoring Using Synthetic Aperture Radar Backscattering Coefficient and Interferometric Coherence

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  • Meriem Barbouchi

    (Sciences and Techniques Laboratory (LR16 INRAT 05), National Institute of Agronomic Researches of Tunisia (INRAT), University of Carthage Agronomic, Tunis 1004, Tunisia)

  • Chayma Chaabani

    (Central Water, Earth and Environment, National Institute for Scientific Research, Quebec, QC G1K 9A9, Canada)

  • Hatem Cheikh M’Hamed

    (Sciences and Techniques Laboratory (LR16 INRAT 05), National Institute of Agronomic Researches of Tunisia (INRAT), University of Carthage Agronomic, Tunis 1004, Tunisia)

  • Riadh Abdelfattah

    (COSIM Lab, Higher School of Communications of Tunis, University of Carthage, Tunis 2083, Tunisia
    ITI Department, Telecom Bretagne, Telecom Institute, 29238 Brest, France)

  • Rachid Lhissou

    (Central Water, Earth and Environment, National Institute for Scientific Research, Quebec, QC G1K 9A9, Canada)

  • Karem Chokmani

    (Central Water, Earth and Environment, National Institute for Scientific Research, Quebec, QC G1K 9A9, Canada)

  • Nadhira Ben Aissa

    (Agronomic Institute of Tunisia (INAT), University of Carthage National, Tunis 1080, Tunisia)

  • Mohamed Annabi

    (Sciences and Techniques Laboratory (LR16 INRAT 05), National Institute of Agronomic Researches of Tunisia (INRAT), University of Carthage Agronomic, Tunis 1004, Tunisia)

  • Haithem Bahri

    (Agronomic Sciences and Techniques Laboratory (LR16 INRAT 05), National Research Institute of Rural Engineering, Water and Forests (INRGREF), University of Carthage, Tunis 1004, Tunisia)

Abstract

Due to the climate change situation, water deficit stress is becoming one of the main factors that threatens the agricultural sector in semi-arid zones. Thus, it is extremely important to provide efficient tools of water deficit monitoring and early detection. To do so, a set of Synthetic Aperture Radar (SAR) backscattering and interferometric SAR (InSAR) Sentinel-1 data, covering the period from January to June 2016, are considered over a durum wheat field in Tunisia. We first studied the temporal variation of the InSAR coherence data and the SAR backscattering coefficient as a function of the phenological stage of the wheat. Subsequently, the parameters of the SAR and InSAR coherence images were analyzed with regard to the water stress coefficient and the wheat height variations. The main findings of this study highlight the high correlation ( r = 0.88 ) that exists between the InSAR coherence and the water stress coefficient, on the one hand, and between the backscattering coefficient, the interferometric coherence, and the water deficit coefficient ( R 2 = 0.95 and R M S E = 14 % ), on the other hand. When a water deficit occurs, the water stress coefficient increases, the crop growth decreases, and the height variation becomes low, and this leads to the increase of the InSAR coherence value. In summary, the reliability of Sentinel-1 SAR and InSAR coherence data to monitor the biophysical parameters of the durum wheat was validated in the context of water deficits in semi-arid regions.

Suggested Citation

  • Meriem Barbouchi & Chayma Chaabani & Hatem Cheikh M’Hamed & Riadh Abdelfattah & Rachid Lhissou & Karem Chokmani & Nadhira Ben Aissa & Mohamed Annabi & Haithem Bahri, 2022. "Wheat Water Deficit Monitoring Using Synthetic Aperture Radar Backscattering Coefficient and Interferometric Coherence," Agriculture, MDPI, vol. 12(7), pages 1-14, July.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:7:p:1032-:d:863271
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    1. Duchemin, B. & Hadria, R. & Erraki, S. & Boulet, G. & Maisongrande, P. & Chehbouni, A. & Escadafal, R. & Ezzahar, J. & Hoedjes, J.C.B. & Kharrou, M.H. & Khabba, S. & Mougenot, B. & Olioso, A. & Rodrig, 2006. "Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices," Agricultural Water Management, Elsevier, vol. 79(1), pages 1-27, January.
    2. Er-Raki, S. & Chehbouni, A. & Guemouria, N. & Duchemin, B. & Ezzahar, J. & Hadria, R., 2007. "Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region," Agricultural Water Management, Elsevier, vol. 87(1), pages 41-54, January.
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    1. Anna Jędrejek & Rafał Pudełko, 2023. "Exploring the Potential Use of Sentinel-1 and 2 Satellite Imagery for Monitoring Winter Wheat Growth under Agricultural Drought Conditions in North-Western Poland," Agriculture, MDPI, vol. 13(9), pages 1-17, September.

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