Articles | Volume 17, issue 7
https://doi.org/10.5194/essd-17-3473-2025
© Author(s) 2025. 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-17-3473-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global agricultural lands in the year 2015
Better Planet Laboratory, University of Colorado, 4001 Discovery Drive, Boulder, CO 80303, USA
Department of Environmental Studies, University of Colorado, 4001 Discovery Drive, Boulder, CO 80303, USA
Institute for Resources, Environment and Sustainability, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
Kaitai Tong
Institute for Resources, Environment and Sustainability, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
School of Public Policy and Global Affairs, University of British Columbia, 6476 NW Marine Drive, Vancouver, BC V6T 1Z2, Canada
Julie Fortin
Institute for Resources, Environment and Sustainability, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
School of Public Policy and Global Affairs, University of British Columbia, 6476 NW Marine Drive, Vancouver, BC V6T 1Z2, Canada
Department of Sustainable Use of Natural Resources, Institute of Social Sciences in Agriculture, University of Hohenheim, Schwerzstraße 40, 70599 Stuttgart, Germany
Radost Stanimirova
Department of Earth and Environment, Boston University, 725 Commonwealth Avenue, Boston, MA 02215, USA
Mark Friedl
Department of Earth and Environment, Boston University, 725 Commonwealth Avenue, Boston, MA 02215, USA
Institute for Resources, Environment and Sustainability, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
School of Public Policy and Global Affairs, University of British Columbia, 6476 NW Marine Drive, Vancouver, BC V6T 1Z2, Canada
Data sets
Geospatial database of global agricultural lands in the year 2015 Zia Mehrabi et al. https://doi.org/10.5281/zenodo.11540553
Short summary
We present a global geospatial database of cropland and pastures for the year 2015. We built these data by fusing satellite-based land cover data with agricultural census data using machine learning. This database is an update to an earlier version representing the year 2000. It can be used to study issues such as land use, food security, climate change, and biodiversity loss. We provide a reproducible code base that can be used to easily update the product for future years.
We present a global geospatial database of cropland and pastures for the year 2015. We built...
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