A new study of Xun County, a National Historic and Cultural City in Hebi, Henan Province, China, offers one of the first quantitative frameworks for measuring how historic districts tell their stories through space. Published in Computational Urban Science, the research combines space syntax, a method for quantifying street-network structure, with agent-based crowd simulation and manual pedestrian counts to diagnose where narrative continuity thrives and where it breaks down across five historic districts in the county’s Old Town.
The team, led by Bin Wang, set out to address a persistent problem in heritage conservation: the disconnection between a district’s physical fabric and its intangible narrative values. Renewal efforts, the authors argue, often overemphasize material effects and commercial development while neglecting the underlying spatial narrative structure. Without an operational, quantitative way to characterize how stories are organized and transmitted across multiple districts, planners risk disrupting narrative continuity and eroding local identity even as they restore buildings.
The framework rests on four space-syntax indicators computed with DepthmapX software. Global integration characterizes system-scale centrality and accessibility, identifying which streets form the cross-district narrative skeleton. Local integration, calculated at radius R3, meaning the area reachable within three turns, captures neighborhood-scale accessibility. Choice predicts the frequency of through-movement, flagging streets likely to serve as connective corridors between districts. Intelligibility, operationalized as the coefficient of determination from a linear regression between local and global integration, measures how readily the overall structure can be inferred from local spatial information, a property tied to wayfinding and cognitive efficiency.
The syntactic analysis produced a strikingly clear picture. Global integration across the Old Town averaged 1.089 and revealed a pronounced north–south gradient. South Street recorded the highest value at 1.256, followed by East Housi Street at 1.182, West Street at 1.136, North Street at 1.065, and East Street at 1.068. These northern axes attract the majority of pedestrian flow and function, in the authors’ terms, as shallow narrative spaces, well suited to directly conveying spatial stories. Southern streets such as North Xiaoximenli Street, with a global integration of 0.937, sit systematically outside the main narrative experience.
Choice values identified the potential narrative corridors that could stitch the fragmented districts together. East Housi Street recorded the highest choice value in the northern part of the Old Town at 179,157, while Pifu Road, at 45,369, emerged as the only high-choice connector in the south. Yet Pifu Road’s continuity is constrained by spatial obstructions, and the study argues that restoring this southern corridor should be the first priority for re-establishing systemic narrative coherence across the whole settlement.
Intelligibility varied sharply among the five districts. South Xiaoximenli Street scored 0.905, East Street 0.776, and Nanshan Street 0.718, all comfortably above the 0.50 threshold the authors treat as the empirical lower limit for practical reference value. North Xiaoximenli Street, at 0.509, fell in the moderate range, while Xinzhuang Street, at 0.427, dropped below the threshold entirely, indicating weak support for spatial comprehension and pedestrian navigation. Values below 0.50 are used in the framework only for trend interpretation, not as an independent basis for intervention.
To test whether structurally central corridors actually attract people, the researchers ran an agent-based simulation in DepthmapX. Agents were released from multiple entrances, including the West Gate, North Gate, CaiYuan Street, South Street, East Housi Street, East Outer Street, and the Pifu Road–Huanghe Road intersection, with populations initialized from observed pedestrian counts. Each agent made independent route decisions based on local information within an R3 radius, weighing shortest-path tendency, local integration strength, and choice value, with added stochasticity to reflect heterogeneous behavior. The simulation ran for 255,000 global time steps, a duration set through pilot tests to reach a stable movement distribution, and was repeated 20 times with different random seeds to account for stochasticity.
The simulation results were then compared with manual pedestrian observations conducted from April 2024 to February 2025 at observation points in all five districts, during four seasonal windows in February, May, August, and November 2024, with daily observation hours fixed at 09:00–12:00, 14:00–18:00, and 19:00–21:00. Two trained volunteers staffed each point, recording entries and exits every ten minutes with handheld counters and rotating hourly to mitigate fatigue-related error. The hotspot patterns from the simulation and the field observations proved largely consistent, with major hotspots overlapping in both datasets.
The comparison also exposed two anomalies that pure syntactic analysis could not explain. North Xiaoximenli Street showed high integration but low simulated flow, with bluish heatmaps away from its intersection with North Street; on-site investigation revealed missing cultural-node signage and illegal structures blocking sightlines. Nanshan Street showed the reverse pattern, low integration but high flow with reddish heatmaps, anchored by religious attributes and historically significant buildings such as the South Gate ruins and the City God Temple. The authors propose these locations as priority narrative anchor points. A separate observation during the temple fair period from February 17 to 19, 2024, immediately after the Lunar New Year, found pedestrian volume on Pifu Road significantly higher than usual, suggesting that cultural events can temporarily activate low-integration areas.
Based on these spatially explicit diagnostics, the study proposes a prioritized, conservation-oriented pathway. In the highly accessible northern districts, where pedestrian and commercial concentration brings risks of over-commercialization and narrative homogenization, renewal should focus on controlling commercial density and preserving culturally distinctive interfaces. In the weaker southern districts, intervention should strengthen north–south linkage and activate culturally meaningful destinations. The recommended sequence is explicit: first remove physical obstructions along Pifu Road to restore connectivity, then implement wayfinding interventions in low-intelligibility areas such as Xinzhuang Street, and finally introduce cultural programming to activate the newly accessible spaces. The authors acknowledge limitations, including the labor-intensive data requirements, the inability of space syntax to capture intangible dimensions such as oral history and local memory, and the reliance on a single case, which constrains generalizability until the framework is tested across multiple sites with different cultural backgrounds and morphological characteristics.
Subject of Research: A quantitative framework combining space syntax and agent-based simulation to assess narrative environments in historic districts
Article Title: 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
Article References: Wang, B. (2026). 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. Computational Urban Science, 6(1), Article 67. https://doi.org/10.1007/s43762-026-00296-z
Image Credits: AI Generated
DOI: 10.1007/s43762-026-00296-z
Keywords: space syntax, agent-based simulation, historic districts, narrative environment, Xun County, urban morphology, pedestrian flow, intelligibility, heritage conservation, spatial accessibility, China, quantitative
News Source: Courtney Benton. (October 27, 2026). Space Syntax and Crowd Simulation Map Storytelling Power of a Chinese Historic Town. Scienmag.
