Fragmented transit governance across multiple agencies makes measuring service inequality in large metropolitan regions notoriously difficult. This paper maps schedule-aware transit service intensity—an origin-side, supply-focused component of accessibility—across the Greater Toronto Area (GTA) by integrating General Transit Feed Specification (GTFS) data from six providers within an H3 hierarchical hexagonal grid. The measure does not capture destination access, travel time, transfers, fares, reliability, or crowding, and is therefore framed throughout as a service-intensity indicator rather than a full accessibility evaluation. We operationalize the indicator as the number of cumulative scheduled departures per hour reachable within an 800 m walking catchment for three distinct time windows: weekday peak, weekday midday, and Saturday midday. Across 9635 hexagons and 23,026 stops, our results reveal a sharply hierarchical regional network. When weighted by population, 16.4% of GTA residents have no scheduled service within walking distance during the weekday morning peak; the corresponding area-weighted share, reflecting the extensive greenbelt and agricultural fringe, is 70.6%. Only 22.6% of hexagons reach at least 12 departures per hour, while 75.5% of residents meet that threshold. Median service intensity drops from 234.25 departures per hour in the Urban Core to zero beyond the Inner Suburban Ring, and service thins out on weekends, with retention in the outer rings dropping to roughly 75% of weekday levels. Spearman correlations show that service intensity is concentrated in denser, more diverse, and lower-income census-tract contexts, with population density emerging as the strongest hex-level correlate (ρ=0.69); after Clifford–Richardson correction for spatial autocorrelation (effective n≈745), the principal CT-level correlations remain statistically significant (p<10−15), and partial correlations controlling for density indicate that socioeconomic composition retains an independent, if attenuated, association. Under one-tract-one-observation aggregation (n=1144 unique tracts), the income gradient strengthens to ρ=−0.74 and becomes co-equal in magnitude with population density (ρ=0.74), confirming that the hex-level coefficients are not artifacts of pseudo-replication. A population-weighted Gini coefficient of 0.60 confirms substantial distributional inequality. Sensitivity analyses confirm that the Inner-to-Outer Suburban break is robust to alternative ring thresholds (10/25/40 and 20/35/50 km), to exclusion of the four Halton municipalities affected by incomplete local-feed coverage, to H3 resolution at the municipal level, and—in a representative shortest-path network sub-analysis for Pickering (not a full GTA-wide network-distance test)—to use of network rather than Euclidean walking distance. These patterns suggest that a substantial gap exists between where suburban residential growth has occurred and where frequent transit service is available, a pattern with historical roots in the 1996–2006 service–need alignment, though the 2006–2023 trajectory is not directly measured here. The results suggest that the transition zone between the inner and outer suburbs may warrant further investigation as a planning focus, and that cross-agency weekend service coordination merits further analysis as a potential equity dimension. This multi-agency H3 framework establishes a reproducible baseline for monitoring schedule-aware service intensity in polycentric metropolitan areas.
Chiranjib Chaudhuri (Tue,) studied this question.