To understand the carbon emission influencing factors of urban land use, the study improves the Kaya equation by analyzing the time-series characteristics of carbon emission from land use and combining it with the improved logarithmic mean division index model to analyze the influencing factors. From the results, the per capita and total carbon emissions from construction land in Shenyang city show an increasing trend in the initial period, followed by a gradual decrease. From 2019 to 2022, the net carbon emissions of Shenyang city decreased from 3165.79*104 tons to 2614.77*104 tons, showing a decreasing trend in this time period. The emission intensity was ranked as construction land, forest land, arable land, grassland, and water. The influencing factor analysis shows that the emission intensity per unit of land has significant inhibitory effects on carbon emissions, with a total contribution of -769.64*104 tons, while GDP per capita and population size become the main factors driving carbon emissions. This suggests that future environmental policies should focus on the transformation of economic development modes and the control of population growth. The research method can effectively analyze the impact of various influencing factors on carbon emissions.