“Accessibility misrepresentation” in public transport

Location-based accessibility is widely assessed using zonal frameworks that aggregate high-resolution results into summary statistics. This aggregation-induced error is often assumed to be negligible, yet this assumption is rarely verified and may obscure critical disparities. This study introduces “Accessibility Misrepresentation” as the deviation between high-resolution accessibility and zonal proxies. Using building-level public transport accessibility in Metropolitan Melbourne, the research evaluates the magnitude, spatial patterns, and equity implications of misrepresentation. Results show systematic variation across travel time thresholds, built environment characteristics, aggregation methods, and service levels. Missed detection of populations without accessibility peaks at 15–20 min thresholds commonly used in neighbourhood accessibility policies, predominantly affecting densely populated middle suburbs where public transport catchments misalign with administrative boundaries. Continuous errors in accessibility values show no systematic directional bias; however, minorities can experience substantial misstatements sufficient to alter normative assessments. Equity analysis reveals disproportionate impacts on middle-status populations often overlooked by conventional frameworks. Population-weighted medians substantially outperform means in reducing misrepresentation. However, no single statistic adequately captures internal variation, particularly with multimodal distributions. A dual-scale approach is recommended: high-resolution computation to characterise within-zone distributions, combined with zonal summaries accompanied by distributional diagnostics, including share of residents without accessibility and upper-tail error indicators. This approach enhances transparency, supports equity-focused and defensible planning decisions without costing additional resources. • Zonal summaries cause “Accessibility Misrepresentation”. • Well-served zones may mask large accessibility gaps. • Middle socioeconomic group has large underserved subpopulations. • Medians outperform means as summaries of zonal accessibility. • Dual-scale analyses expose disparities and preserve interpretability.