Optimal Use of Multi-Sensor Data for Precision Agriculture: Sentinel-1 and Sentinel-2 Fusion in Crop Classification

maryam choukri; ahmed laamrani; abdelghani chehbouni

doi:https://doi.org/10.5194/egusphere-egu25-12795

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EGU25-12795, updated on 15 Mar 2025

https://doi.org/10.5194/egusphere-egu25-12795

EGU General Assembly 2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Optimal Use of Multi-Sensor Data for Precision Agriculture: Sentinel-1 and Sentinel-2 Fusion in Crop Classification

maryam choukri¹, ahmed laamrani^1,2,3, and abdelghani chehbouni^1,2

maryam choukri et al.

¹mohammed VI polytechnic university, Centre for remote sensing applications , Morocco (maryam.choukri@um6p.ma)
²College Agriculture and Environmental Sciences, Mohammed VI Polytechnic University (UM6P), Benguerir 43150, Morocco
³Department of Geography, Environment & Geomatics, University of Guelph, Guelph, ON N1G 2W1, Canada

How to cite: choukri, M., laamrani, A., and chehbouni, A.: Optimal Use of Multi-Sensor Data for Precision Agriculture: Sentinel-1 and Sentinel-2 Fusion in Crop Classification, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12795, https://doi.org/10.5194/egusphere-egu25-12795, 2025.

This abstract has been withdrawn on 25 Jul 2025.