A quantitative framework for assessing narrative environments in historic districts using space syntax and agent-based crowd simulation: a case study of Xun County, China

This study proposes a quantitative framework for assessing narrative environments in historic districts by integrating space syntax with agent-based simulation (ABS). Taking five historic districts in the Old Town of Xun County, China, as the case study, the research combines global integration, local integration, choice, and intelligibility to identify spatial accessibility, corridor potential, and cognitive efficiency, and uses ABS together with manual pedestrian observations to validate movement concentration and detect anomalous areas. Syntactic analysis identifies East Housi Street and South Street as the primary movement corridors, with the highest accessibility (global integration = 1.182 and 1.256, respectively) and pedestrian concentration, whereas Xinzhuang Street exhibits critically weak connectivity (intelligibility R 2 = 0.427), while Pifu Road emerges as an important southern corridor (choice = 45,369) whose continuity is constrained by spatial obstructions. The results reveal a clear north–south gradient in spatial accessibility: northern districts exhibit higher accessibility and stronger pedestrian concentration, but also greater risks of over-commercialization and narrative homogenization, whereas southern districts are characterized by corridor fragmentation, weaker accessibility, and disrupted cultural continuity. ABS validation reveals two anomalies: North Xiaoximenli (low flow despite moderate syntax, blocked by illegal structures) and Nanshan (high traffic despite low syntax, anchored by the City God Temple). Based on these spatially explicit diagnostics, the proposed framework provides an evidence-based priority pathway for removing physical obstructions, reactivating southern heritage nodes, and restoring corridor continuity along East Housi Street, offering a replicable technical pathway for spatial diagnosis, narrative restoration, and conservation-oriented renewal in multi-district historic environments.