Improving vitality has been a major bottleneck in the revitalization of traditional village heritage worldwide. The vitality of traditional village (VTV) varies greatly depending on socioeconomic factors and natural conditions. Significant spatial variation exists in VTV, even within the same urban jurisdictions in China; however, the main determinants for this have not yet been quantified owing to the difficulty of obtaining data from large rural samples, making targeted invigoration difficult. Thus, we applied point of interest data, which are easily accessible big data, to bridge the data source gap. To assess the VTV’s influencing factors and analyze the spatial variations among the factors’ impacting intensity, we used the Ordinary Least Squares and Geographically Weighted Regression models and conducted empirical studies involving 148 traditional villages in Lishui, China. Seven factors influenced the vitality of traditional villages in the study area, with the most significant being topographic relief, elevation, scenic spots and commercial industry. Moreover, the factors’ impacting intensity varied by region. Topographic relief and elevation had the greatest impact intensity in the north and south of Lishui, whereas primary education, transportation facility and agricultural bases had the greatest impact in the north, and scenic spots and commercial industry had the greatest impact in the middle of Lishui. Taken together, this method makes a large sample of VTV’s impact factor analysis feasible, has global implications, and can provide a foundation for the scientific and precise regional promotion of VTV, which is beneficial for rural heritage revitalization.