This article constructed a multidimensional urban sprawl measurement index system from the structural dimension, morphological dimension, density dimension, and efficiency dimension. Based on map visualization, standard deviation ellipse, and cold and hot spot analysis, it explored the spatiotemporal characteristics and migration evolution patterns of China's urban comprehensive sprawl from 2005 to 2020. The spatiotemporal geographically weighted model (GTWR) was used to empirically examine the spatiotemporal heterogeneity of the impact of multidimensional urban sprawl on carbon emission intensity. Research shows that: (1) The comprehensive urban sprawl in China exhibited a spatial difference of "high in the east and low in the west", but the urban sprawl in the eastern coastal and northeastern regions has declined in the later stage of the sample. The standard deviation ellipse shows a trend of centripetal clustering, and the center of gravity of the distribution shifts towards the southwest as a whole. The analysis of hot and cold spots presents regional differences of "hot in the east and cold in the west". (2) The overall urban sprawl has a significant impact on carbon emissions, and over time, it plays a positive promoting role in an increasing number of cities. The positive promotion area is mainly concentrated in the central and western regions and coastal areas, while the negative inhibition area is mainly the North China Plain and the Pearl River Delta. (3) There is significant spatiotemporal heterogeneity in the influencing factors of each dimension. In terms of temporal trends, the structural dimension promotes carbon emissions in most cities and its influence increases year by year; The form dimension has shifted from a promoting effect to a inhibiting effect on carbon emissions in most cities; The density dimension and efficiency dimension suppress carbon emissions in most cities, but the density dimension shows a polarization trend year by year, while the influence of the efficiency dimension weakens overall. In terms of spatial distribution, the influence of structural dimension and density dimension is stronger in the southeastern, western, and northeastern regions, while the significant effect of morphological dimension is in the northeastern border and central western regions, and the significant effect of efficiency dimension is in the central and western regions.