The unrealised potential of agroforestry (Raw drone images GHA 2022 Part B)

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 (Part B) includes imagery from farms P71 to P180, collected in 2022 as part of a stratified sampling design in Ghana. It is one of several folders containing raw drone imagery—unprocessed aerial photographs (JPEGs)—captured during field surveys across cocoa farms in Ghana between 2021 and 2022. These images were collected as part of a broader effort to map shade-tree cover and aboveground biomass using drone-based ground-truth data and machine learning. The raw images in this folder served as the basis for generating orthomosaics, digital surface models, digital terrain models, and vegetation height estimates.