Satellite data enable estimation of harvest volumes and carbon emissions from Congo Basin logging
摘要
Selective logging is widespread in tropical forests, yet its extent, intensities, and impacts are poorly understood. Here we developed estimates of annual timber harvest volumes, carbon emissions, and potential emissions reductions for 2020–2024 for industrial logging concessions in six Congo Basin countries. Using 62 harvest observations, we calibrated a model linking logging road development and forest disturbance detection data to harvest volumes, generating predictions at multiple spatial scales. Regional harvests averaged 14.7 M cubic meters per year and produced emissions of 87.5 teragrams carbon dioxide per year. Reduced-impact logging practices could cut emissions by 35–58%, generating $309–489 M per year in climate financing. Our harvest estimates differ from national statistics (125% higher for Gabon, 81% lower for Democratic Republic of the Congo) and our road development emissions estimates differ from previous sample-based accounting (73% lower for region). These timely, spatially-explicit data support sustainability assessment, regulatory compliance, certification efforts, and climate mitigation strategies, and our methods are broadly applicable to tropical forests with selective logging.