Abstract
Surface soil moisture is a key parameter of crop monitoring, water stress detection and irrigation management, particularly in the mediterranean region where the water resources are very limited. The aim of the study is the synergy of radar Sentinel-1 and optical Sentinel-2 data for surface soil moisture (SSM) retrieval over wheat crops. The backscattering coefficient derived from Sentinel-1, is modeled using the Water Cloud Model (WCM) combined with Oh model. The normalized difference vegetation index (NDVI) computed from Sentinel-2 is used as descriptor of vegetation in the WCM. The combined model is calibrated and validated using Sentiel-1/2 data and in situ measurement collected from two irrigated wheat fields located in the Haouz plain in the center of Morocco. The calibration is done at VV and VH polarizations and at 35.2° and 45.6° of incidence angles. Hereafter, an inversion approach is developed basing on the combined model for surface soil moisture retrieval. Results showed that SSM is retrieved with significant statistical metrics at VV polarization with R = 0.65, RMSE = 0.08 m3/m3, and bias = −0.01 m3/m3 at 35.2° of incidence angle and R = 0.57, RMSE = 0.09 m3/m3 and bias = 0.01 m3/m3 at 45.6°.
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Acknowledgements
This work is conducted within the frame of the International Joint Laboratory TREMA (https://www.lmi-trema.ma/). The authors wish to thank the projects: IRRIWEL (Prima S2), RISE-H2020-ACCWA and ERANETMED03-62 CHAAMS.
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Ouaadi, N., Ezzahar, J., Jarlan, L., Khabba, S., Frison, P.L. (2023). Synergy of Sentinel-1 and Sentinel-2 Satellites for Surface Soil Moisture Retrieval Over Wheat Crops in Semi-arid Areas. In: Bekkay, H., Mellit, A., Gagliano, A., Rabhi, A., Amine Koulali, M. (eds) Proceedings of the 3rd International Conference on Electronic Engineering and Renewable Energy Systems. ICEERE 2022. Lecture Notes in Electrical Engineering, vol 954. Springer, Singapore. https://doi.org/10.1007/978-981-19-6223-3_63
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DOI: https://doi.org/10.1007/978-981-19-6223-3_63
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