Selected publications

Mohamed Bourriz
  • Bourriz, M.; Hajji, H.; Laamrani, A.; Elbouanani, N.; Abdelali, H.A.; Bourzeix, F.; El-Battay, A.; Amazirh, A.; Chehbouni, A. Integration of Hyperspectral Imaging and AI Techniques for Crop Type Mapping: Present Status, Trends, and Challenges. Remote Sens. 2025, 17, 1574. https://doi.org/10.3390/rs17091574External link
  • Bourriz, M., Laamrani, A., Ait Abdelali, H., Bourzeix, F., El-Battay, A., Amazirh, A., et Chehbouni, A. : How Effective Are Foundation Models for Crop Type Mapping Using Hyperspectral Imaging? A Comparative Study of Machine Learning, Deep Learning, and Geospatial Foundation Models, GeoAdvances25, Marrakech, Morocco, 29–30 May 2025.
  • Elbouanani, N., Laamrani, A., El-Battay, A., Hajji, H., Bourriz, M., Bourzeix, F., Ait Abdelali, H., Amazirh, A., and Chehbouni, A.: Enhancing Soil Fertility Mapping with Hyperspectral Remote Sensing and Advanced AI: A Comparative Study of Dimensionality Reduction Techniques in Morocco, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18418, https://doi.org/10.5194/egusphere-egu25-18418, 2025.
  • El Bouanani, N.; Laamrani, A.; Hajji, H.; Bourriz, M.; Bourzeix, F.; Ait Abdelali, H.; El-Battay, A.; Amazirh, A.; Chehbouni, A. Estimating Soil Attributes for Yield Gap Reduction in Africa Using Hyperspectral Remote Sensing Data with Artificial Intelligence Methods: An Extensive Review and Synthesis. Remote Sens. 2025, 17, 1597. https://doi.org/10.3390/rs17091597External link
  • Bourriz, M., Laamrani, A., El-Battay, A., Hajji, H., Elbouanani, N., Ait Abdelali, H., Bourzeix, F., Amazirh, A., and Chehbouni, A.: An Intercomparison of Two Satellite-Based Hyperspectral Imagery (PRISMA & EnMAP) for Agricultural Mapping: Potential of these sensors to produce hyperspectral time-series essential for tracking crop phenology and enhancing crop type mapping, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18417, https://doi.org/10.5194/egusphere-egu25-18417, 2025.