The unrealised potential of agroforestry (Raw drone images GHA 2022 High Shade Part A)

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 (High Shade Part A) includes imagery from farms H05 to H67, collected in 2022 in Ghana. These farms were not selected using the original stratified sampling design, but were instead targeted specifically for their higher shade levels. 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.