Deforestation remains one of the most significant sources of greenhouse gas emissions globally. Tropical regions are particularly critical to climate mitigation due to their high carbon density and ongoing conversion to agricultural uses. While earth observation (EO) has become fundamental for assessing land-use change over time and space, key gaps persist in understanding associated carbon emissions (CE) and their distribution across production systems, information required by diverse international and European policy frameworks targeting greenhouse gas reduction and deforestation. To address this, the study integrates satellite-derived aboveground biomass (AGB) with machine learning-based land-use modeling to quantify commodity-specific CE from deforestation in Colombia. Our key findings reveal that pasture expansion for livestock dominates emissions (>67% in the Amazonas and Orinoquía regions, approximately 25% nationally), while cocoa and coffee, despite smaller cultivation areas, exhibit high emission factors (>25% of subregional totals in the Andes, Pacífico, and Caribe). Smallholder croplands contribute up to 16.7% regionally, and oil palm plays a modest role nationally. These results underscore the importance of targeting both extensive pasture systems and high-emission perennial crops in deforestation-free supply chain policies, while considering the diverse regional land-use dynamics. In conclusion, our framework offers spatially explicit, crop-specific emission estimates that address essential gaps in EO-based CE quantification. It provides clear, actionable baselines for monitoring policies aimed at promoting deforestation-free supply chains, such as the EU Deforestation Regulation (EUDR), across tropical landscapes. Ultimately, this data supports the creation of a comprehensive database of country-specific emission factors, a resource critical for enhancing national carbon inventories, guiding policy decisions related to high-risk deforestation commodities, and ensuring more transparent and traceable zero-deforestation supply chains.

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