Vol. 6 No. 02 (2025)
Articles

Analyzing Transit Stop Service Areas Using Geographic Information Systems (GIS): A Case Study of UET Taxila

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  • Muhammad Salman,
  • Muhammad Arshad,
  • Muhammad Noman,
  • Sami Ullah Khan,
  • Afaq Ahmed,
  • Muzammal Hussain
Muhammad Salman
University of Quebec at Rimouski, Canada
Muhammad Arshad
Civil Engineering Department, UET Taxila, Pakistan
Muhammad Noman
University of Florida, Gainesville, USA
Sami Ullah Khan
Urban Unit-Urban Sector Planning & Management Services Unit (Pvt.) Limited, Lahore, Pakistan
Afaq Ahmed
Oslo Metropolitan University, Norway
Muzammal Hussain
UET Taxila, Pakistan
DOI: https://doi.org/10.38094/jocef602110

Published 2025-09-28

Keywords

  • Transportation Planning,
  • Transit Stop Analysis,
  • Geographical Information System ,
  • GIS,
  • Walking Time,
  • Service Area Assessment
    • ...More
    Less

How to Cite

[1]
M. . Salman, M. . Arshad, M. . Noman, S. . Ullah Khan, A. . Ahmed, and M. . Hussain, “Analyzing Transit Stop Service Areas Using Geographic Information Systems (GIS): A Case Study of UET Taxila”, JoCEF, vol. 6, no. 02, pp. 97-102, Sep. 2025.

Copyright (c) 2025

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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Abstract

The University of Engineering and Technology Taxila (UET Taxila), established in 1975 as a campus of the University of Engineering and Technology Lahore, is a leading public university in Taxila, Punjab, Pakistan. With a transportation network spanning approximately 518 square kilometers across Islamabad, Rawalpindi, and Wah Cantt, it provides an economical and efficient transit system for students, faculty, and staff. This study evaluates the service area coverage of transit stops using Geographic Information Systems (GIS) to assess network efficiency, accessibility, and spatial gaps. At the university, 16 buses operate across 16 routes, serving an average of 810 users daily. The analysis defines transit stop service areas based on 5, 10, and 15-minute walking times, assuming a walking speed of 100 meters per minute. Results reveal that 69% of users access transit stops within a walkable distance, while 31% rely on other modes of transport. Among those with walking access, 27% reach a stop in under 5 minutes, 23% within 5 to 10 minutes, and 19% within 10 to 15 minutes. These findings provide valuable insights for optimizing the university's transportation network and supporting future transit planning decisions

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