A Multi-Scale Analysis of Public Space in Peri-Urban Plain-Type Villages in Shanxi from a Spatial–Behavioral Coupling Perspective

Against the backdrop of two-way urban–rural flows and the development of rural tourism, public space in peri-urban plain-type villages now carries multiple functions at the same time, including everyday life, visitor stay, and spatial display. As a result, the relationship between spatial organization and actual use has become increasingly complex. Taking Xihuaiyuan Village on the outskirts of Taiyuan as a case study, this paper builds a four-scale analytical framework covering the village, street, node, and element scales. It integrates social network analysis (SNA), space syntax, behavioral path analysis, questionnaire and interview data, and image–text perception data collected from Weibo, Xiaohongshu, Mafengwo, Dianping, and Ctrip to examine the structural characteristics, actual use, and spatial representation of rural public space, and further introduces spatial–behavioral coupling analysis at the node scale. The results show that there is a clear structure–behavior mismatch in the public-space system of Xihuaiyuan Village. The physical spatial network is more connected than the behavioral network. At the street level, the village has formed a configurational hierarchy led by a small number of streets with high integration and high choice. At the node level, functional use differs between villagers and tourists: villagers tend to prefer nodes with stronger social functions, while tourists rely more on sightseeing-oriented hubs. These nodes can be further divided into four types: synergistic, structure-Led, behavior-led, and dual-low marginal type. Spatial attraction is mainly concentrated in visual elements such as murals and flower landscapes, whereas cultural depth and service facilities receive much less attention. From the perspective of spatial–behavioral interaction, this study proposes a multi-scale, multi-source coupling framework, which may provide a useful reference for the differentiated identification and optimization of rural public space.