Association Between Morphological Spatial Patterns of Built-Up Land and Carbon Emissions: Evidence from 303 Cities in China

Given the accelerated growth of built-up land, optimizing land-use patterns is a practical strategy for reducing urban carbon emissions. While previous studies have concentrated on landscape patterns, the association between the morphological spatial pattern (MSPA) of built-up land and carbon emissions remains unknown. The MSPA not only captures the fine-scale characteristics of land use but also provides direct guidance for urban planning. To fill this gap, we took China, the world’s largest carbon-emitting country, as a case study. First, the MSPA of built-up land was identified from multitemporal land-use data for 2005, 2010, 2015, and 2018. Next, a covariance analysis was conducted to identify the control variables that are significantly associated with carbon emissions. Finally, we innovatively integrated the MSPA with machine learning techniques to explore the association between the MSPA of built-up land and carbon emissions, thereby overcoming the limitations of traditional landscape indices. The results demonstrate an increasingly evident decoupling effect between carbon emissions and socioeconomic growth in China, while the MSPA factors played increasingly significant roles. In particular, a “network” configuration of built-up land is more conducive to low-carbon city planning than compact development. Additionally, the merging of “islets” into “cores” should be avoided. Our findings highlight the growing importance of the MSPA in carbon reduction and can shed light on the spatial design of built-up land.