Spatiotemporal Heterogeneity of Land-Use Landscape Pattern Effects on CO 2 Emissions at the City-Level Scale in China

Climate change has emerged as a critical global issue. Land-use/cover change (LUCC) plays a pivotal role in influencing terrestrial ecosystem carbon cycles and further regulates carbon emission intensity by reshaping the spatial characteristics of landscape patterns. Taking 300 Chinese cities as the study area, an analytical framework encompassing carbon emission accounting, regional land-use landscape pattern analysis, spatiotemporal correlation between landscape patterns and carbon emissions, and economic “core-periphery” disparities was presented. The land-use carbon emissions and landscape pattern indices of each city from 2005 to 2020 were calculated, and the geographically weighted regression (GWR) model was employed to examine the impact of land-use landscape pattern changes on carbon emissions from an urban perspective. Furthermore, the cities were categorized into developed and underdeveloped groups based on the median per capita GDP to compare how economic development levels moderate this impact mechanism. The results indicate that the relationship between landscape patterns and carbon emissions exhibits significant spatial heterogeneity, highlighting the complexity of the influence of land-use morphology on carbon emissions. Sustainable land-use strategies must account for regional disparities in economic levels, planning capacity, and administrative characteristics rather than pursuing a uniform urban form. Economic development significantly moderates the carbon mitigation effects of landscape patterns through its influence on spatial governance capacity, leading to pronounced differences between cities at varying development levels. Moving forward, regionally tailored approaches that integrate landscape optimization with industrial transformation and ecological conservation should be prioritized to provide spatial solutions for achieving the carbon peaking and carbon neutrality goals.