Evidence map›Paper›PMID 41882013›Full record

ArticleScientific data2026

Crop and irrigation types ground-truth dataset for Moroccan agricultural regions.

Youness Ouassanouan, Jamal Elfarkh, Said Grich, Abderrahman Liblab, Abdelghani Chehbouni

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In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Youness OuassanouanCenter for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir, 43150, Morocco. youness.ouassanouan@um6p.ma.
Jamal ElfarkhCenter for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir, 43150, Morocco.
Said GrichCenter for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir, 43150, Morocco.
Abderrahman LiblabCenter for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir, 43150, Morocco.
Abdelghani ChehbouniCenter for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir, 43150, Morocco.

Funding

OCP Group project FIRMA, A Flexible and Innovative Field-Scale Decision Support Platform for Irrigation Management, (grant n°AS140)
6 · The paper itself

Abstract

Accurate information on crop types and irrigation systems is a fundamental input for improving our understanding of land-atmosphere interactions and monitoring agricultural dynamics in semi-arid environments. This paper presents a comprehensive, open-access ground-truth dataset of 10000 geolocated agricultural parcels collected across the five major agricultural regions of Morocco, El Gharb, Tadla, Doukkala, El Haouz, and Souss, between December 2023 and January 2025. The dataset encompasses 45 distinct crop types, including main seasonal crops such as wheat, corn, and alfalfa, as well as perennial crops including olives, citrus, and argan. In addition, six different irrigation systems were observed, from the traditional flood irrigation to advanced pivot systems, reflecting the diversity of Moroccan agro-ecosystems. Field data were collected using the GIS-based mobile application QField, ensuring high positional accuracy and detailed attribute information for each parcel. To evaluate dataset consistency, Normalized Difference Vegetation Index (NDVI) values were analyzed for all surveyed plots throughout 2024, revealing coherent seasonal dynamics in agricultural activity. Each record is accompanied by a geo-referenced photograph, providing an additional visual reference for validation and contextual understanding. The freely available dataset offers a high-quality reference for calibrating and validating Earth Observation (EO)-based crop type and irrigation mapping products. By representing the diversity of cropping systems and irrigation practices across Morocco's climatic zones, this dataset provides a valuable foundation for advancing EO-driven agricultural monitoring, supporting policy assessment, and promoting sustainable land and water management in Morocco and the wider North African region.

Identifiers

PMID41882013
PMCPMC13181056

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.