Abstract: The accurate evaluation of rural vulnerability and identification of its spatial differentiation is the basis for rational development planning and accurate implementation of the strategies to promote rural revitalization. Focused on the problem that the weight distribution of efficiency model affects the accuracy of evaluation results, this research studied the framework of stress shock chain analysis with the introduction of disaster vulnerability theory to define the regional social-ecological system vulnerability connotation and formation mechanism. Three kinds of efficiency evaluation models were used to evaluate and compare 184 administrative villages in Qingpu District of Shanghai in 2018, and the comprehensive ranking method of 'vulnerability grade-fragile spatial agglomeration characteristic-fragile size' was used to design the sequence of integrated territory consolidation. The obtained results are as follows: (1) The formative process of formation of the combined capacity of the regional social-ecological systems to respond to the differences in vulnerability, resistance, adaptability and resiliency in combination with the change of 'environment-socio-economic' pressure was consistent with the vulnerability efficiency of 'pressure input-capacity output'. (2) The EW-ACE-DEA model based on entropy weight aggregation was more reliable and accurate for the evaluation of regional social-ecological system vulnerability. In the year of 2018, the average social-ecological system vulnerability of the administrative village in this region was 0.595, the range of the whole region was0.404, 0.787, and the spatial trend was gradually decreasing from east to west. (3) According to the comprehensive ranking method of the regional vulnerability grade and the spatial agglomeration characteristic and value of vulnerability, the sequence of integrated territory consolidation in this area can be reasonably planned. The comprehensive regulation of administrative villages in Qingpu District can be divided into five categories: short-term (33 villages), short-medium-term (45 villages), medium-term (41 villages), medium-long-term (38 villages) and long-term (27 villages). The research results could enrich the theory of rural geography and provide decision basis for rural regional governance, rural revitalization and regional sustainable development.