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The Skeletal Trap: Mapping Spatial Inequality and Ghost Stops in Ankara's Transit Network

Elifnaz Kancan

Abstract

Ankara's public transport crisis is commonly framed as a shortage of buses or operational inefficiency. This study argues that the problem is fundamentally morphological and structural. The city's leapfrog urban expansion has produced fragmented peripheral clusters disconnected from a rigid, center-oriented bus network. As a result, demand remains intensely concentrated along the Kizilay-Ulus axis and western corridors, while peripheral districts experience either chronic under-service or enforced transfer dependency. The deficiency is therefore not merely quantitative but rooted in the misalignment between urban macroform and network architecture. The empirical analysis draws on a 173-day operational dataset derived from route-level passenger and trip reports published by EGO under the former "Transparent Ankara" initiative. To overcome the absence of stop-level geospatial data, a Connectivity-Based Weighted Distribution Model reallocates passenger volumes to 1 km x 1 km grid cells using network centrality. The findings reveal persistent center-periphery asymmetries, structural bottlenecks, and spatially embedded accessibility inequalities.

The Skeletal Trap: Mapping Spatial Inequality and Ghost Stops in Ankara's Transit Network

Abstract

Ankara's public transport crisis is commonly framed as a shortage of buses or operational inefficiency. This study argues that the problem is fundamentally morphological and structural. The city's leapfrog urban expansion has produced fragmented peripheral clusters disconnected from a rigid, center-oriented bus network. As a result, demand remains intensely concentrated along the Kizilay-Ulus axis and western corridors, while peripheral districts experience either chronic under-service or enforced transfer dependency. The deficiency is therefore not merely quantitative but rooted in the misalignment between urban macroform and network architecture. The empirical analysis draws on a 173-day operational dataset derived from route-level passenger and trip reports published by EGO under the former "Transparent Ankara" initiative. To overcome the absence of stop-level geospatial data, a Connectivity-Based Weighted Distribution Model reallocates passenger volumes to 1 km x 1 km grid cells using network centrality. The findings reveal persistent center-periphery asymmetries, structural bottlenecks, and spatially embedded accessibility inequalities.
Paper Structure (9 sections, 4 equations, 12 figures, 2 tables)

This paper contains 9 sections, 4 equations, 12 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Methodology and Analytical Framework
  3. Step 1: Stop Connectivity Score ($C_s$).
  4. Step 2: Route Aggregate Connectivity ($C_{\text{total}}(r)$).
  5. Step 3: Stop Weight Coefficient ($W_s(r)$).
  6. Step 4: Final Passenger Distribution ($P_s(r)$).
  7. Spatial Analysis & Mapping
  8. Conclusion
  9. Limitations

Figures (12)

  • Figure 1: Urban Activity Proxy (Nighttime Lights): Heatmap illustrating Ankara's leapfrog expansion and peripheral clusters outpacing traditional transit infrastructure in 2025.LightPollutionMap_Ankara.
  • Figure 2: Radar chart illustrating the distinct algorithmic fingerprints of the three grid categories, demonstrating that Critical Grids (red) uniquely exhibit simultaneous failure across both static anomaly detection (left) and dynamic regime stability (right) axes, while Anomaly Only and Regime Shift Only categories display mutually exclusive failure patterns
  • Figure 3: Daily Passenger Count Trends and Temporal Anomalies
  • Figure 4: Heatmap of daily occupancy rates for the 20 most volatile routes, highlighting extreme fluctuations
  • Figure 5: Spatial Distribution of Average Occupancy Rates: A grid-based visualization identifying extreme localized saturation (red zones) in peripheral districts such as Sincan and Batıkent, highlighting where demand exceeds available supply.
  • ...and 7 more figures