Data

The unrealised potential of agroforestry (Maps of agro-climatic zones)

The University of Queensland
Dr Simon Hart (Aggregated by) Dr Wilma J. Blaser Hart (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/844d738&rft.title=The unrealised potential of agroforestry (Maps of agro-climatic zones)&rft.identifier=RDM ID: 1cb74d6b-9e4b-44a8-976a-267c7eeb0d88&rft.publisher=The University of Queensland&rft.description=This dataset is part of a larger collection supporting the analysis in Becker et al., Nature Sustainability (2025) on the climate mitigation potential of cocoa agroforestry in West Africa. The full dataset is published via UQ eSpace as a series of interlinked records, each representing a different stage of the research workflow—from raw imagery to processed data products and analysis code. This subset contains a GeoTIFF raster layer of agro-climatic zones (ACZ maps) covering Ghana and Côte d’Ivoire, derived from long-term climate data (1990–2020). These zones represent distinct agro-climatic types, each showing unique patterns of cocoa suitability across the region.&rft.creator=Dr Simon Hart&rft.creator=Dr Wilma J. Blaser Hart&rft.date=2025&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Sustainable agricultural development&rft_subject=Agriculture, land and farm management&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Agroforestry&rft_subject=Forestry sciences&rft_subject=Deep learning&rft_subject=Machine learning&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft.type=dataset&rft.language=English Access the data
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[email protected]
School of the Environment

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This dataset is part of a larger collection supporting the analysis in Becker et al., Nature Sustainability (2025) on the climate mitigation potential of cocoa agroforestry in West Africa. The full dataset is published via UQ eSpace as a series of interlinked records, each representing a different stage of the research workflow—from raw imagery to processed data products and analysis code. This subset contains a GeoTIFF raster layer of agro-climatic zones (ACZ maps) covering Ghana and Côte d’Ivoire, derived from long-term climate data (1990–2020). These zones represent distinct agro-climatic types, each showing unique patterns of cocoa suitability across the region.

Issued: 2025

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Subjects
Agricultural, Veterinary and Food Sciences | Agriculture, Land and Farm Management | Agroforestry | Deep Learning | Forestry Sciences | Information and Computing Sciences | Machine Learning | Sustainable Agricultural Development | eng |

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Identifiers
ACN 633 798 857