Ouassanouan et al. (2026) Crop and irrigation types ground-truth dataset for Moroccan agricultural regions

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-03-25
• Authors: Youness Ouassanouan, Jamal Elfarkh, said grich, Abderrahman Liblab, Abdelghani Chehbouni
• DOI: 10.1038/s41597-026-06993-y

Research Groups

• Center for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir, Morocco

Short Summary

This paper presents a comprehensive, open-access ground-truth dataset comprising 10,000 geolocated agricultural parcels in Morocco, detailing 45 crop types and 6 irrigation systems, to serve as a high-quality reference for calibrating and validating Earth Observation-based agricultural monitoring products.

Objective

• To provide a comprehensive, open-access ground-truth dataset of crop types and irrigation systems for Moroccan agricultural regions to improve understanding of land-atmosphere interactions and monitor agricultural dynamics in semi-arid environments, specifically for calibrating and validating Earth Observation (EO)-based mapping products.

Study Configuration

• Spatial Scale: Five major agricultural regions of Morocco: El Gharb, Tadla, Doukkala, El Haouz, and Souss.
• Temporal Scale: Field data collected between December 2023 and January 2025; Normalized Difference Vegetation Index (NDVI) values analyzed throughout 2024 for consistency evaluation.

Methodology and Data

• Models used: No user-defined code or specific models (e.g., ISBA, mHM) were generated or used for data collection; analyses were performed using standard software tools and publicly available resources.
• Data sources: Ground-truth field observations of 10,000 geolocated agricultural parcels collected using the GIS-based mobile application QField, supplemented by geo-referenced photographs for each record. Normalized Difference Vegetation Index (NDVI) analysis was used for dataset consistency evaluation.

Main Results

• A comprehensive, open-access ground-truth dataset of 10,000 geolocated agricultural parcels was created for five major agricultural regions in Morocco.
• The dataset includes 45 distinct crop types, covering main seasonal crops (e.g., wheat, corn, alfalfa) and perennial crops (e.g., olives, citrus, argan).
• Six different irrigation systems, ranging from traditional flood to advanced pivot systems, are documented within the dataset.
• Field data collection utilized the GIS-based mobile application QField, ensuring high positional accuracy and detailed attribute information for each parcel.
• Dataset consistency was evaluated through Normalized Difference Vegetation Index (NDVI) analysis for all surveyed plots throughout 2024, demonstrating coherent seasonal dynamics in agricultural activity.
• Each record in the dataset is accompanied by a geo-referenced photograph, providing additional visual reference for validation and contextual understanding.
• The dataset is publicly available via a repository (https://doi.org/10.6084/m9.figshare.28486022.v2).

Contributions

• Provides a high-quality, comprehensive, and open-access ground-truth reference dataset for calibrating and validating Earth Observation (EO)-based crop type and irrigation mapping products in semi-arid environments.
• Represents the diversity of cropping systems and irrigation practices across Morocco’s climatic zones, offering a valuable foundation for advancing EO-driven agricultural monitoring.
• Supports policy assessment and promotes sustainable land and water management in Morocco and the wider North African region.

Funding

• Project FIRMA, A Flexible and Innovative Field-Scale Decision Support Platform for Irrigation Management (grant n°AS140, funded by the OCP group).
• Project Aqueduct PRIMA-2166.

Citation

@article{Ouassanouan2026Crop,
  author = {Ouassanouan, Youness and Elfarkh, Jamal and grich, said and Liblab, Abderrahman and Chehbouni, Abdelghani},
  title = {Crop and irrigation types ground-truth dataset for Moroccan agricultural regions},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-026-06993-y},
  url = {https://doi.org/10.1038/s41597-026-06993-y}
}