Articles | Volume 16, issue 2
https://doi.org/10.5194/essd-16-867-2024
© Author(s) 2024. 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-16-867-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
09 Feb 2024
Data description article |
| 09 Feb 2024
| 09 Feb 2024
GloCAB: global cropland burned area from mid-2002 to 2020
Joanne V. Hall
CORRESPONDING AUTHOR
Department of Geographical Sciences, University of Maryland, College Park, MD, USA
Fernanda Argueta
Department of Geographical Sciences, University of Maryland, College Park, MD, USA
Maria Zubkova
Department of Geographical Sciences, University of Maryland, College Park, MD, USA
Yang Chen
Department of Earth System Science, University of California, Irvine, CA, USA
James T. Randerson
Department of Earth System Science, University of California, Irvine, CA, USA
Louis Giglio
Department of Geographical Sciences, University of Maryland, College Park, MD, USA
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Cited
32 citations as recorded by crossref.
- Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model M. Forrest et al. https://doi.org/10.5194/bg-21-5539-2024
- From fields to policy: analyzing the interplay between technology adoption and residue burning in Punjab, India E. Gupta et al. https://doi.org/10.1088/2976-601X/ae7a75
- A Weakly Supervised Multi-Scale Cross-Modal Information Fusion Method for Wildfire Detection D. Wen et al. https://doi.org/10.3390/computers15050311
- Substantial discrepancies across global fire emissions inventories: a systematic intercomparison J. Yang et al. https://doi.org/10.1016/j.jes.2026.105563
- Review of agricultural biomass burning and its impact on air quality in the continental United States of America S. Pinakana et al. https://doi.org/10.1016/j.envadv.2024.100546
- Tillage and biomass detection for estimating winter-time cropland management practices with satellite remote sensing M. Yli-Heikkilä et al. https://doi.org/10.1080/22797254.2025.2525967
- Landscape fires and decreasing carbon sequestration capacity: Quantifying greenhouse gas emissions due to the Russo–Ukrainian war R. Vasylyshyn et al. https://doi.org/10.1016/j.ecolind.2025.114453
- Influence of country development levels and agricultural burning policies on global cropland biomass burning observed from satellites S. An et al. https://doi.org/10.1088/1748-9326/ae1b1d
- Estimating cropland fire emissions with remote sensing: A literature review and data strategy C. Dahman et al. https://doi.org/10.1051/e3sconf/202567603002
- Accelerating learning and impact in conservation by tailoring learning and adaptive management approaches to the stage of strategy development S. Reddy et al. https://doi.org/10.1111/csp2.70117
- Accelerated reduction in China's cropland fires against the background of policy enhancement C. Lian et al. https://doi.org/10.1016/j.eiar.2024.107512
- Landscape fire emissions from the 5th version of the Global Fire Emissions Database (GFED5) G. van der Werf et al. https://doi.org/10.1038/s41597-025-06127-w
- A survival guide for assessing global fire risks to natural and human systems C. Steinmann et al. https://doi.org/10.1016/j.ijdrr.2026.106140
- Integrated leaching-steam explosion pretreatment to upgrade low-grade biomass into high-quality black pellets B. Samal et al. https://doi.org/10.1016/j.renene.2026.125749
- BuRNN (v1.0): a data-driven fire model S. Lampe et al. https://doi.org/10.5194/gmd-19-955-2026
- The NASA VIIRS burned area product, global validation, and intercomparison with the NASA MODIS burned area product L. Giglio et al. https://doi.org/10.1016/j.rse.2025.115006
- The Influence of Australian Bushfire on the Upper Tropospheric CO and Hydrocarbon Distribution in the South Pacific D. Lee et al. https://doi.org/10.3390/rs17122092
- Increase in carbon monoxide (CO) and aerosol optical depth (AOD) observed by satellites in the Northern Hemisphere over the summers of 2008–2023, linked to an increase in wildfires A. Ehret et al. https://doi.org/10.5194/acp-25-6365-2025
- HSRRSFPD and MEGRDNet: empowering high-resolution farmland parcel mapping in complex terrains Y. Yan et al. https://doi.org/10.1016/j.jag.2026.105346
- The Global Forest Fire Emissions Prediction System version 1.0 K. Anderson et al. https://doi.org/10.5194/gmd-17-7713-2024
- Model fires, not ignitions: Capturing the human dimension of global fire regimes M. Kasoar et al. https://doi.org/10.1016/j.crsus.2024.100128
- Enhanced CH4 emissions from global wildfires likely due to undetected small fires J. Zhao et al. https://doi.org/10.1038/s41467-025-56218-w
- Two decades of fire activity over the PEEX domain: a look from space, with contribution from models and ground-based measurements L. Sogacheva et al. https://doi.org/10.1080/20964471.2024.2316730
- Impacts of El Niño–Southern Oscillation on global fire PM2.5 during 2000–2023 Y. Hu et al. https://doi.org/10.1016/j.aosl.2025.100597
- A global behavioural model of human fire use and management: WHAM! v1.0 O. Perkins et al. https://doi.org/10.5194/gmd-17-3993-2024
- GloCAB cropland field boundary dataset J. Hall et al. https://doi.org/10.1016/j.dib.2024.110739
- Evaluation of global fire simulations in CMIP6 Earth system models F. Li et al. https://doi.org/10.5194/gmd-17-8751-2024
- Small-scale livelihood and cultural fire: Global spatiotemporal characteristics, and gaps in data C. Smith et al. https://doi.org/10.1371/journal.pone.0339561
- Artificial intelligence with earth observations provides continuous streamflow data across varying wildfire recurrence and recovery scenarios S. Uddin et al. https://doi.org/10.1016/j.envsoft.2026.106989
- Deep learning for wildfire risk prediction: Integrating remote sensing and environmental data Z. Xu et al. https://doi.org/10.1016/j.isprsjprs.2025.06.002
- Temporal and Spatial Dynamics of Summer Crop Residue Burning Practices in North China: Exploring the Influence of Climate Change and Anthropogenic Factors S. Yin et al. https://doi.org/10.3390/rs16244763
- Landsat-based fire maps reveal higher fire emissions from larger area of low-severity burnings than coarse resolution data in Southeast Asia M. Xiahou & Z. Shen https://doi.org/10.1016/j.jag.2025.104815
32 citations as recorded by crossref.
- Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model M. Forrest et al. https://doi.org/10.5194/bg-21-5539-2024
- From fields to policy: analyzing the interplay between technology adoption and residue burning in Punjab, India E. Gupta et al. https://doi.org/10.1088/2976-601X/ae7a75
- A Weakly Supervised Multi-Scale Cross-Modal Information Fusion Method for Wildfire Detection D. Wen et al. https://doi.org/10.3390/computers15050311
- Substantial discrepancies across global fire emissions inventories: a systematic intercomparison J. Yang et al. https://doi.org/10.1016/j.jes.2026.105563
- Review of agricultural biomass burning and its impact on air quality in the continental United States of America S. Pinakana et al. https://doi.org/10.1016/j.envadv.2024.100546
- Tillage and biomass detection for estimating winter-time cropland management practices with satellite remote sensing M. Yli-Heikkilä et al. https://doi.org/10.1080/22797254.2025.2525967
- Landscape fires and decreasing carbon sequestration capacity: Quantifying greenhouse gas emissions due to the Russo–Ukrainian war R. Vasylyshyn et al. https://doi.org/10.1016/j.ecolind.2025.114453
- Influence of country development levels and agricultural burning policies on global cropland biomass burning observed from satellites S. An et al. https://doi.org/10.1088/1748-9326/ae1b1d
- Estimating cropland fire emissions with remote sensing: A literature review and data strategy C. Dahman et al. https://doi.org/10.1051/e3sconf/202567603002
- Accelerating learning and impact in conservation by tailoring learning and adaptive management approaches to the stage of strategy development S. Reddy et al. https://doi.org/10.1111/csp2.70117
- Accelerated reduction in China's cropland fires against the background of policy enhancement C. Lian et al. https://doi.org/10.1016/j.eiar.2024.107512
- Landscape fire emissions from the 5th version of the Global Fire Emissions Database (GFED5) G. van der Werf et al. https://doi.org/10.1038/s41597-025-06127-w
- A survival guide for assessing global fire risks to natural and human systems C. Steinmann et al. https://doi.org/10.1016/j.ijdrr.2026.106140
- Integrated leaching-steam explosion pretreatment to upgrade low-grade biomass into high-quality black pellets B. Samal et al. https://doi.org/10.1016/j.renene.2026.125749
- BuRNN (v1.0): a data-driven fire model S. Lampe et al. https://doi.org/10.5194/gmd-19-955-2026
- The NASA VIIRS burned area product, global validation, and intercomparison with the NASA MODIS burned area product L. Giglio et al. https://doi.org/10.1016/j.rse.2025.115006
- The Influence of Australian Bushfire on the Upper Tropospheric CO and Hydrocarbon Distribution in the South Pacific D. Lee et al. https://doi.org/10.3390/rs17122092
- Increase in carbon monoxide (CO) and aerosol optical depth (AOD) observed by satellites in the Northern Hemisphere over the summers of 2008–2023, linked to an increase in wildfires A. Ehret et al. https://doi.org/10.5194/acp-25-6365-2025
- HSRRSFPD and MEGRDNet: empowering high-resolution farmland parcel mapping in complex terrains Y. Yan et al. https://doi.org/10.1016/j.jag.2026.105346
- The Global Forest Fire Emissions Prediction System version 1.0 K. Anderson et al. https://doi.org/10.5194/gmd-17-7713-2024
- Model fires, not ignitions: Capturing the human dimension of global fire regimes M. Kasoar et al. https://doi.org/10.1016/j.crsus.2024.100128
- Enhanced CH4 emissions from global wildfires likely due to undetected small fires J. Zhao et al. https://doi.org/10.1038/s41467-025-56218-w
- Two decades of fire activity over the PEEX domain: a look from space, with contribution from models and ground-based measurements L. Sogacheva et al. https://doi.org/10.1080/20964471.2024.2316730
- Impacts of El Niño–Southern Oscillation on global fire PM2.5 during 2000–2023 Y. Hu et al. https://doi.org/10.1016/j.aosl.2025.100597
- A global behavioural model of human fire use and management: WHAM! v1.0 O. Perkins et al. https://doi.org/10.5194/gmd-17-3993-2024
- GloCAB cropland field boundary dataset J. Hall et al. https://doi.org/10.1016/j.dib.2024.110739
- Evaluation of global fire simulations in CMIP6 Earth system models F. Li et al. https://doi.org/10.5194/gmd-17-8751-2024
- Small-scale livelihood and cultural fire: Global spatiotemporal characteristics, and gaps in data C. Smith et al. https://doi.org/10.1371/journal.pone.0339561
- Artificial intelligence with earth observations provides continuous streamflow data across varying wildfire recurrence and recovery scenarios S. Uddin et al. https://doi.org/10.1016/j.envsoft.2026.106989
- Deep learning for wildfire risk prediction: Integrating remote sensing and environmental data Z. Xu et al. https://doi.org/10.1016/j.isprsjprs.2025.06.002
- Temporal and Spatial Dynamics of Summer Crop Residue Burning Practices in North China: Exploring the Influence of Climate Change and Anthropogenic Factors S. Yin et al. https://doi.org/10.3390/rs16244763
- Landsat-based fire maps reveal higher fire emissions from larger area of low-severity burnings than coarse resolution data in Southeast Asia M. Xiahou & Z. Shen https://doi.org/10.1016/j.jag.2025.104815
Saved (final revised paper)
Latest update: 24 Jul 2026
Short summary
Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
Crop-residue burning is a widespread practice often occurring close to population centers. Its...
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