Abstract
Anthropogenic activities have altered approximately two‐thirds of the Earth's land surface. Urbanization, industrialization, agricultural expansion, and deforestation are increasingly impacting the terrestrial landscapes, leading to shifts of areas in artificial surface (i.e., humanmade), cropland, pasture, forest, and barren land. Land use patterns and associated greenhouse gas (GHG) emissions play a critical role in global climate change. Here we synthesized 29 years of global historical data and demonstrated how land use impacts global GHG emissions using structural equation modeling. We then obtained predictive estimates of future global GHG emissions using a deep learning model. Our results show that, from 1992 to 2020, the global terrestrial areas covered by artificial surface and cropland have expanded by 133% and 6% because of population growth and socioeconomic development, resulting in 4.0% and 3.8% of declines in pasture and forest areas, respectively. Land use was significantly associated with GHG emissions ( p 2 eq from 1992 to 2020. Looking ahead, if current trends in global land use continue at the same rates, our model projects that global GHG emissions will reach 76 ± 8 GtCO 2 eq in 2050. In contrast, reducing the rates of land use change by half could limit global GHG emissions to 60 ± 3 GtCO 2 eq in 2050. Monitoring and analyzing these projections allow a better understanding of the potential impacts of various land use scenarios on global climate and planning for a sustainable future.