Deciphering Land Use-Carbon Emissions-Economy Nexus: Decoupling dynamics and sustainable planning pathways

Elucidating the systemic nexus among land use, carbon emissions, and the economy is critical for advancing the global Sustainable Development Goals, particularly those addressing climate change, social progress, and effective governance. This study introduces a land-use subdivision method grounded in the sources of carbon emissions and the composition of GDP, thereby enabling the functional classification of land use in China, the world’s largest carbon emitter and second-largest economy. This approach reveals the marginal effects and characteristic curves of land use on economic and emission indicators while elucidating the underlying mechanisms. A dimension-reduction algorithm tailored for large-scale, multi-class geographic grid processing is developed, enabling the historical characterization of carbon emissions at China’s tertiary administrative level from 2010 to 2025, and predictions for 2030, the China’s target carbon peak year. This study uncovers several notable conclusions: (1) industrial land has been the largest contributor to historical emissions, and maintaining its area below 333.82 km2 is conducive to achieving decoupling at the city scale, (2) the marginal effect of mixed commercial-residential land on GDP surpasses its impact on carbon emissions, suggesting that integrating commercial-service land (26.09 km2) with urban residential land (39.04 km2) facilitates decoupling, (3) this study demonstrates that relocating industrial land effectively mitigates emissions at the agglomeration scale while concurrently impairing regional development equity, and (4) a total of 163 cities and 1,384 counties in China are identified as being at risk of negative decoupling, with their poverty alleviation potential assessed from the perspective of land resource allocation and expansion. Broader context: Achieving global sustainability necessitates integrated insights into greenhouse gas emissions (SDGs 7, 13, and 15), equitable socioeconomic development (SDGs 1, 8, and 10), and effective urban governance (SDGs 9 and 11). This study introduces the Land Use–Carbon Emissions–Economy Nexus, an interdisciplinary framework leveraging remote sensing, geographic information systems, machine learning, energy science, and social science to reveal the coupled dynamics among land-use planning, greenhouse gas emissions, and socioeconomic systems. The framework enables a multiscale decoupling analysis and supports informed and sustainable regional planning.