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<p>A well-planned and developed transportation network is essential for accessibility and mobility in a city. An efficient transportation network can reduce energy demand through optimal routes and traffic flow. A geospatial network analysis enables the quantitative assessment of network topology through metrics such as centrality, clustering coefficient, and density. In this work, the integration of graph theory and GIS was explored to characterize and analyze the road network of Ranchi City, India. Multiple network connectivity indices are utilized to assess road network topology and its structural properties. Specifically, Alpha, Beta, Gamma, Detour, Eta, Pi, Theta, Grid-Tree indices, and the Cyclomatic number are treated as criterion variables to calculate weights using the Analytic Hierarchy Process (AHP). OpenStreetMap data were modelled in a GIS environment to derive connectivity indices. The findings reveal significant spatial variations in connectivity and efficiency across different wards. Central wards of the city exhibit higher connectivity, while peripheral areas demonstrate lower accessibility. The average value for Alpha index was 0.017, for Beta index 0.0187, for Gamma index 0.461, for detour index 0.86, for grid tree proportion index 0.73, for Theta index 0.13, for eta index 0.076, for Pi index is 15.12, and for cyclomatic no. is 253.49. After applying AHP to these values, we obtain an average efficiency score of 0.45, depicted as the flow efficiency coefficient, and a connectivity score of 0.432, depicted as the topological resilience factor. The findings highlight the need for targeted infrastructure development to address spatial disparities, improved network efficiency, and enhanced accessibility in underserved areas. By optimizing connectivity and traffic flow, the study contributes to reducing transport-related energy demand, aligning with SDG 7 (affordable and clean energy). These insights support evidence-based urban planning for more sustainable, efficient, and equitable transportation system in Ranchi city.</p>

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An integrated spatial approach using graph theory and analytic hierarchy process for assessing transportation network efficiency and connectivity in Ranchi city, India

  • 期刊论文

  • 发表日期：

    2026年4月24日

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  • Triyan Kumar Roy,
  • Varun Narayan Mishra,
  • Maya Kumari,
  • Thota Sivasankar,
  • Rajendra Prasad,
  • Padam Jee Omar

摘要

A well-planned and developed transportation network is essential for accessibility and mobility in a city. An efficient transportation network can reduce energy demand through optimal routes and traffic flow. A geospatial network analysis enables the quantitative assessment of network topology through metrics such as centrality, clustering coefficient, and density. In this work, the integration of graph theory and GIS was explored to characterize and analyze the road network of Ranchi City, India. Multiple network connectivity indices are utilized to assess road network topology and its structural properties. Specifically, Alpha, Beta, Gamma, Detour, Eta, Pi, Theta, Grid-Tree indices, and the Cyclomatic number are treated as criterion variables to calculate weights using the Analytic Hierarchy Process (AHP). OpenStreetMap data were modelled in a GIS environment to derive connectivity indices. The findings reveal significant spatial variations in connectivity and efficiency across different wards. Central wards of the city exhibit higher connectivity, while peripheral areas demonstrate lower accessibility. The average value for Alpha index was 0.017, for Beta index 0.0187, for Gamma index 0.461, for detour index 0.86, for grid tree proportion index 0.73, for Theta index 0.13, for eta index 0.076, for Pi index is 15.12, and for cyclomatic no. is 253.49. After applying AHP to these values, we obtain an average efficiency score of 0.45, depicted as the flow efficiency coefficient, and a connectivity score of 0.432, depicted as the topological resilience factor. The findings highlight the need for targeted infrastructure development to address spatial disparities, improved network efficiency, and enhanced accessibility in underserved areas. By optimizing connectivity and traffic flow, the study contributes to reducing transport-related energy demand, aligning with SDG 7 (affordable and clean energy). These insights support evidence-based urban planning for more sustainable, efficient, and equitable transportation system in Ranchi city.