Full description
This dataset is part of a larger collection accompanying the analysis presented in “The unrealized potential of agroforestry for an emissions-intensive agricultural commodity” (Becker et al., Nature Sustainability, 2025). The full dataset has been 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 raw drone imagery—unprocessed aerial photographs (JPEGs)—collected during field surveys in the Guiglo area of western Côte d’Ivoire. Drone flights were conducted across cocoa farms in this region in 2021, as part of a broader effort to map shade-tree cover using drone-based ground-truth data and machine learning. The images in this folder served as the basis for generating orthomosaics, digital surface models, digital terrain models, and vegetation height estimates. Fieldwork in Abengourou was carried out in collaboration with the Sustainable Cocoa Initiative Support Programme (SCISP) and the Sustainable Agricultural Supply Chains Initiative (SASI, formerly INA) of the German Development Agency (GIZ).Issued: 2025
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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Other Information
Identifiers
- Local : RDM ID: f4ae6afa-3e19-4700-9fa0-48802b0679df
- DOI : 10.48610/D45B49F
