Abstract: Identifying the spatial differentiation characteristics and underlying driving mechanisms of the vulnerability to relative poverty in the Liupanshan area-a contiguous poverty-stricken area-during the post-poverty alleviation era will help provide a scientific basis for optimizing China's rural revitalization strategy. By integrating the geographical capital theory with the Bogardi-Birkmann-Cardona (BBC) framework, this study established a three-dimensional (3D) assessment system that incorporates ecological exposure, social sensitivity, and economic adaptability. Based on multi-source remote sensing and statistical data, the spatial differentiation characteristics and underlying driving mechanisms of the vulnerability to relative poverty in the Liupanshan area were analyzed using spatial analysis, the Geodetector model, and the K-means clustering algorithm. The findings indicate that the vulnerability to relative poverty in the Liupanshan area exhibits prominent spatial agglomeration. Based on the spatial distribution differences of indices across various dimensions, zones with vulnerability to relative poverty in the Liupanshan area can be divided into ecological exposure-dominated, ecological-social, social-economic, and potential vulnerable zones. Four primary factors driving vulnerability to relative poverty were identified: the proportion of migrant workers, normalized difference vegetation index (NDVI), rural employment level, and average elevation. Besides superior indicator simplicity and model interpretability, the 3D assessment system established for the vulnerability to relative poverty provides a tool for monitoring and preventing relapse into poverty and holds potential for application in similar areas.