Investigating the spatial differentiation characteristics of soil organic carbon （SOC） in regional agricultural land and analyzing its driving factors are important for screening auxiliary variables for SOC prediction in agricultural land and the accurate prediction of soil carbon stock. This study considered SOC in different types of agricultural land landscape complexes in Beijing as the research object. The differences in SOC content and its stock in different landscape complexes were explored based on the long-term positional monitoring data on the quality of cultivated land in Beijing and the field sampling and testing data. Utilizing multi-source and open-source data as environmental variables that affected SOC spatial differentiation, we explored the quantitative and spatial relationships between SOC and climate, topography, soil parent material, land use, and biomass factors in different landscape complexes through GeoDetector and geographically weighted regression modeling. Additionally, we constructed a structural equation model to reveal the pathways that influence each driving factor on SOC in terms of direct and indirect effects. Ultimately, the major controlling factors of SOC were identified in the study area. The results showed that： ① The mean values of