Mapping the Coupling Coordination Between China’s Digital Economy and Carbon Emissions: Spatiotemporal Patterns and Spatial Markov Transitions

Against the backdrop of accelerating global digitalization and mounting climate pressures, enabling digital-economy growth while simultaneously controlling carbon emissions has become a critical challenge for China. This study constructs a Digital Economy Development Index (DEI) and a Carbon Emissions Index (CEI) to examine the spatiotemporal evolution and spatial heterogeneity of coordinated development between the digital economy and carbon emissions. We employ global and local Moran’s I, a spatial Markov chain model, and kernel density estimation to investigate spatiotemporal autocorrelation, interregional transition patterns, and the dynamic evolution of the coupling coordination degree over 2011–2022. The results indicate that China’s eastern region performs notably better in achieving coordinated development, maintaining persistently higher coupling coordination levels. In contrast, the central and western regions face substantial challenges; in particular, low-value areas exhibit considerable potential to transition toward higher-value states, suggesting substantial room for improvement. The spatiotemporal analysis further reveals pronounced regional disparities and provides a scientific basis for policymaking aimed at advancing green and low-carbon development strategies tailored to regional characteristics.