An open dataset for assessing the deforestation footprint linked to bio-commodity trade

We present here a dataset obtained with the Python package deforestfoot, which assesses the deforestation impacts associated with the trade of commodities identified by the EU Deforestation-free Products Regulation (EUDR), plus maize, established in 2023. Deforestfoot's typical outputs are forest loss, deforestation attribution, land footprint, and embodied deforestation associated with the trade of bio-based commodities, using both national statistics (FAOSTAT) and Earth Observation (EO) data. Wood/timber-related results are not currently included in this release, due to high uncertainty in current methodologies for attributing deforestation and degradation to timber trade. Cattle-related outputs carry substantially higher uncertainty than other commodities, primarily due to diet composition assumptions used in the land footprint calculation. This dataset is organised into five subfolders, including the input data needed to run the package. The file dataset_file_list.csv lists all files in the dataset, together with their primary source. The dataset is subdivided into four folders according to the methodology implemented, plus one folder containing metadata: Land use: change in forest, cropland, pasture, and forest plantation area reported using FAOSTAT data. Land use balance model: forest loss due to the expansion of cropland, pasture, and planted forest assessed using both statistical data and EO following the model proposed by Pendrill et al. (2019). Land footprint: associated with the trade of EUDR products. Several inputs together with deforestfoot output and intermediate results from De Laurentiis et al. (2024) are available here. Embodied deforestation: associated with consumption at country level, including results across multiple methodological scenarios used for uncertainty quantification. Metadata: containing product mapping tables and country codes.