Abstract: Under the concept of green and low-carbon development, it is of great significance to explore the spatial-temporal characteristics and the influencing factors of the efficiency of “cutting carbon, reducing pollution, expanding green” for urban land. Based on a panel dataset covering 108 cities from 2003 to 2021 in the Yangtze River Economic Belt, the undesirable output super-efficiency SBM model, kernel density estimation, spatial autocorrelation analysis, and spatial panel econometric models were used in this study. Findings found that: (1) The efficiency values showed an overall upward trend, with values rising from 0.338 in 2003 to 0.677 in 2021. These valuesshowed stage-specific characteristics in regional disparities and widening intercity differences, along with polarization phenomena. (2) Positive spatial autocorrelation was evident at the global level, whereas at the local scale, four types of agglomeration patterns were identified, i.e. high-high, low-low, low-high, and high-low. (3) A significant positive spatial spillover effect was confirmed, where a 1% increase in efficiency of “cutting carbon, reducing pollution, expanding green” induced a 0.155% rise in neighboring cities. (4) Spatial effect decomposition disclosed varying direct and indirect effects of influencing factors on the efficiency. Therefore, it was necessary to consider the spatial correlations and spillover effects among cities to enhance the efficiency of urban land changes in the Yangtze River Economic Belt.