Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-4997-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-4997-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Nov 2023
Data description paper |
| 15 Nov 2023
| 15 Nov 2023
A new cropland area database by country circa 2020
Francesco N. Tubiello
CORRESPONDING AUTHOR
Statistics Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy
Giulia Conchedda
Statistics Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy
Leon Casse
Statistics Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy
Pengyu Hao
Digitalization and Informatics Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy
Giorgia De Santis
Statistics Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy
Zhongxin Chen
Digitalization and Informatics Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy
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Total article views: 3,247 (including HTML, PDF, and XML)
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Cited
14 citations as recorded by crossref.
- A 2020 forest age map for China with 30 m resolution K. Cheng et al. 10.5194/essd-16-803-2024
- An annual cropland extent dataset for Africa at 30 m spatial resolution from 2000 to 2022 Z. Lou et al. 10.5194/essd-17-3777-2025
- Uncertainties in carbon emissions from land use and land cover change in Indonesia I. Brasika et al. 10.5194/bg-22-3547-2025
- Remote sensing for crop mapping: A perspective on current and future crop-specific land cover data products C. Zhang et al. 10.1016/j.rse.2025.114995
- The potential of irrigation for cereals production in Sub–Saharan Africa: A machine learning application for emulating crop growth at large scale A. Klinnert et al. 10.1016/j.agwat.2025.109488
- Pesticides application rate maps in the European Union at a 250 m spatial resolution G. Porta et al. 10.1038/s41597-025-05031-7
- Indirect Land use Change Mechanisms: Tests from Biofuel Mandates and Pantropical Agriculture V. Guye 10.1007/s10640-025-01020-x
- CROPGRIDS: a global geo-referenced dataset of 173 crops F. Tang et al. 10.1038/s41597-024-03247-7
- Climate-driven global cropland changes and consequent feedbacks N. You et al. 10.1038/s41561-025-01724-1
- Continental maize mapping and distribution in Africa by integrating radar and optical imagery N. Abdelrahim & S. Jin 10.1007/s10661-025-14502-8
- Assessing the Consistency of Five Remote Sensing-Based Land Cover Products for Monitoring Cropland Changes in China F. Deng et al. 10.3390/rs16234498
- Accuracy Comparison and Synergistic Strategies of Seven High-Resolution Cropland Maps (1–10 m) in China X. Peng et al. 10.3390/rs17173121
- A new cropland area database by country circa 2020 F. Tubiello et al. 10.5194/essd-15-4997-2023
- Dynamic global-scale crop and irrigation monitoring L. See et al. 10.1038/s43016-023-00841-7
12 citations as recorded by crossref.
- A 2020 forest age map for China with 30 m resolution K. Cheng et al. 10.5194/essd-16-803-2024
- An annual cropland extent dataset for Africa at 30 m spatial resolution from 2000 to 2022 Z. Lou et al. 10.5194/essd-17-3777-2025
- Uncertainties in carbon emissions from land use and land cover change in Indonesia I. Brasika et al. 10.5194/bg-22-3547-2025
- Remote sensing for crop mapping: A perspective on current and future crop-specific land cover data products C. Zhang et al. 10.1016/j.rse.2025.114995
- The potential of irrigation for cereals production in Sub–Saharan Africa: A machine learning application for emulating crop growth at large scale A. Klinnert et al. 10.1016/j.agwat.2025.109488
- Pesticides application rate maps in the European Union at a 250 m spatial resolution G. Porta et al. 10.1038/s41597-025-05031-7
- Indirect Land use Change Mechanisms: Tests from Biofuel Mandates and Pantropical Agriculture V. Guye 10.1007/s10640-025-01020-x
- CROPGRIDS: a global geo-referenced dataset of 173 crops F. Tang et al. 10.1038/s41597-024-03247-7
- Climate-driven global cropland changes and consequent feedbacks N. You et al. 10.1038/s41561-025-01724-1
- Continental maize mapping and distribution in Africa by integrating radar and optical imagery N. Abdelrahim & S. Jin 10.1007/s10661-025-14502-8
- Assessing the Consistency of Five Remote Sensing-Based Land Cover Products for Monitoring Cropland Changes in China F. Deng et al. 10.3390/rs16234498
- Accuracy Comparison and Synergistic Strategies of Seven High-Resolution Cropland Maps (1–10 m) in China X. Peng et al. 10.3390/rs17173121
Latest update: 17 Oct 2025
Short summary
We describe a new dataset of cropland area circa the year 2020, with global coverage and country detail. Data are generated from geospatial information on the agreement characteristics of six high-resolution cropland maps. By helping to highlight features of cropland characteristics and underlying causes for agreement across land cover products, the dataset can be used as a tool to help guide future mapping efforts towards improved agricultural monitoring.
We describe a new dataset of cropland area circa the year 2020, with global coverage and country...
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