PERCEIVING THE CITY FROM THE TRAIN: A REGRESSION MODELLING BASED ASSESSMENT OF PASSENGERS’ VISUAL EXPERIENCE OF RAILWAY STATION APPROACHES

Abstract

Railway stations and the surrounding areas serve as crucial urban thresholds; the visual information that passengers are exposed to as they approach shapes their perception of the city as a whole and their initial impressions (Lunardon et al., 2023a). This study quantifies the perceptual factors that influence the visual quality perceived by the travellers while approaching station areas, through the train windows. We deployed twelve visual-quality indicators and modelled their relationship into an overall visual-perception score using a survey of 100 respondents from five case-study railway stations (Amritsar, Kalka, Chandigarh, Shimla, and Ludhiana). An ordered-logit model and ordinary least squares (OLS) regression were both estimated. The findings suggest that while texture variation and material quality have mixed or weak associations in OLS estimates, other factors frequently highlighted in design guidelines, such as coherence/flow, proportionality of built elements, and lighting, show positive associations with the overall visual perception. Diagnostics show strong directional signals that are helpful for design interventions, but modest explanatory power (see Table 3). The study makes two contributions: (1) a reproducible empirical framework for converting qualitative visual-quality indicators into quantitative predictors; and (2) policy-relevant implications for station-area design guidelines that prioritize landscape/cleanliness management, legible spatial sequencing, and visibility of cultural features. Site-specific suggestions and directions for cross-cultural and longitudinal extensions are included in the manuscript's conclusion.