Research Article
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Year 2024, Volume: 5 Issue: 1, 17 - 21, 31.07.2024
https://doi.org/10.53635/jit.1501395

Abstract

References

  • Yang, H., & Liang, Y. (2023). Examining the Connectivity between Urban Rail Transport and Regular Bus Transport. Sustainability, 15(9), 7644. https://doi.org/10.3390/su15097644
  • Çapalı, B., & Ceylan, H. (2020). Effect of walking and waiting times on travel time. Journal of Innovative Transportation, 1(2), 1202.
  • Terzi, S., & Erten, K. M. (2020). The effect of big data analysis for sustainable transportation. Journal of Innovative Transportation, 1(1), 1102.
  • May, A. D. (2015). Encouraging good practice in the development of Sustainable Urban Mobility Plans. Case studies on transport policy, 3(1), 3-11. https://doi.org/10.1016/j.cstp.2014.09.001
  • Yue, Y., Wang, W., Chen, J., & Du, Z. (2021). Evaluating the capacity coordination in the urban multimodal transport network. Applied Sciences, 11(17), 8109. https://doi.org/10.3390/app11178109
  • Friedrich, M. (2016). Evaluating the service quality in multi-modal transport networks. Transportation Research Procedia, 15, 100-112. https://doi.org/10.1016/j.trpro.2016.06.009
  • Song, J., Abuduwayiti, A., & Gou, Z. (2023). The role of subway network in urban spatial structure optimization–Wuhan city as an example. Tunnelling and Underground Space Technology, 131, 104842. https://doi.org/10.1016/j.tust.2022.104842
  • Guo, Y., Yang, L., Lu, Y., & Zhao, R. (2021). Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence. Sustainable Cities and Society, 65, 102594. https://doi.org/10.1016/j.scs.2020.102594
  • Wu, X., Lu, Y., Gong, Y., Kang, Y., Yang, L., & Gou, Z. (2021). The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space. Journal of transport geography, 97, 103215. https://doi.org/10.1016/j.jtrangeo.2021.103215
  • Li, S., Yang, H., Zhang, G., Ling, Z., Xiong, Y., & Li, Y. (2019, July). What is the best catchment area of a metro station? A study based on station level ridership modeling. In 2019 5th International Conference on Transportation Information and Safety (ICTIS) (pp. 1239-1244). IEEE. https://doi.org/10.1109/ICTIS.2019.8883789
  • El-Geneidy, A., Grimsrud, M., Wasfi, R., Tétreault, P., & Surprenant-Legault, J. (2014). New evidence on walking distances to transit stops: Identifying redundancies and gaps using variable service areas. Transportation, 41, 193-210. https://doi.org/10.1007/s11116-013-9508-z
  • O'Sullivan, S., & Morrall, J. (1996). Walking distances to and from light-rail transit stations. Transportation Research Record, 1538(1), 19-26.
  • Kim, T., Sohn, D. W., & Choo, S. (2017). An analysis of the relationship between pedestrian traffic volumes and built environment around metro stations in Seoul. KSCE Journal of Civil Engineering, 21, 1443-1452. https://doi.org/10.1007/s12205-016-0915-5
  • Pekdemir, M. I., Altintasi, O., & Ozen, M. (2024). Assessing the Impact of Public Transportation, Bicycle Infrastructure, and Land Use Parameters on a Small-Scale Bike-Sharing System: A Case Study of Izmir, Türkiye. Sustainable Cities and Society, 101, 105085. https://doi.org/10.1016/j.scs.2023.105085
  • Maas, S., Attard, M., & Caruana, M. A. (2020). Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria. Transportation Research Part A: Policy and Practice, 140, 81-97. https://doi.org/10.1016/j.tra.2020.08.003
  • Wu, Y., Li, W., Yu, Q., & Li, J. (2022). Analysis of the Relationship between Dockless Bicycle‐Sharing and the Metro: Connection, Competition, and Complementation. Journal of Advanced Transportation, 2022(1), 5664004. https://doi.org/10.1155/2022/5664004
  • Tresidder, M. (2005). Using GIS to measure connectivity: An exploration of issues. Portland State University: Field Area Paper, 1-43.
  • Zacharias, J., & Zhao, Q. (2018). Local environmental factors in walking distance at metro stations. Public Transport, 10, 91-106. https://doi.org/10.1007/s12469-017-0174-y
  • Gan, Z., Yang, M., Feng, T., & Timmermans, H. J. (2020). Examining the relationship between built environment and metro ridership at station-to-station level. Transportation Research Part D: Transport and Environment, 82, 102332. https://doi.org/10.1016/j.trd.2020.102332
  • Sun, G., Zacharias, J., Ma, B., & Oreskovic, N. M. (2016). How do metro stations integrate with walking environments? Results from walking access within three types of built environment in Beijing. Cities, 56, 91-98. https://doi.org/10.1016/j.cities.2016.03.001
  • Zhao, J., Deng, W., Song, Y., & Zhu, Y. (2013). What influences Metro station ridership in China? Insights from Nanjing. Cities, 35, 114-124. https://doi.org/10.1016/j.cities.2013.07.002
  • Dill, J. (2004). Measuring network connectivity for bicycling and walking. In 83rd annual meeting of the Transportation Research Board, Washington, DC (pp. 11-15).

Investigation of the road network structure around rail transit stations

Year 2024, Volume: 5 Issue: 1, 17 - 21, 31.07.2024
https://doi.org/10.53635/jit.1501395

Abstract

This study examined the connectivity of road networks around rail transit stations in İzmir, Türkiye, using intersection density and connected node ratio metrics. The analysis was conducted within 800 m, 600 m, and 400 m catchment areas around these stations, which were considered reasonable walking distances. Rail transit stations and road networks were digitized using ArcGIS Pro software. The research identified variations in connectivity scores among different stations and buffer zones. Stations in high-density areas like Konak and those near the ferry port showed higher connectivity scores, indicating well-integrated street networks that support multimodal transportation. In contrast, stations such as Ataşehir and Mavişehir, where intersection densities were lower, demonstrated significant connectivity challenges, underscoring the necessity for targeted urban planning interventions.

References

  • Yang, H., & Liang, Y. (2023). Examining the Connectivity between Urban Rail Transport and Regular Bus Transport. Sustainability, 15(9), 7644. https://doi.org/10.3390/su15097644
  • Çapalı, B., & Ceylan, H. (2020). Effect of walking and waiting times on travel time. Journal of Innovative Transportation, 1(2), 1202.
  • Terzi, S., & Erten, K. M. (2020). The effect of big data analysis for sustainable transportation. Journal of Innovative Transportation, 1(1), 1102.
  • May, A. D. (2015). Encouraging good practice in the development of Sustainable Urban Mobility Plans. Case studies on transport policy, 3(1), 3-11. https://doi.org/10.1016/j.cstp.2014.09.001
  • Yue, Y., Wang, W., Chen, J., & Du, Z. (2021). Evaluating the capacity coordination in the urban multimodal transport network. Applied Sciences, 11(17), 8109. https://doi.org/10.3390/app11178109
  • Friedrich, M. (2016). Evaluating the service quality in multi-modal transport networks. Transportation Research Procedia, 15, 100-112. https://doi.org/10.1016/j.trpro.2016.06.009
  • Song, J., Abuduwayiti, A., & Gou, Z. (2023). The role of subway network in urban spatial structure optimization–Wuhan city as an example. Tunnelling and Underground Space Technology, 131, 104842. https://doi.org/10.1016/j.tust.2022.104842
  • Guo, Y., Yang, L., Lu, Y., & Zhao, R. (2021). Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence. Sustainable Cities and Society, 65, 102594. https://doi.org/10.1016/j.scs.2020.102594
  • Wu, X., Lu, Y., Gong, Y., Kang, Y., Yang, L., & Gou, Z. (2021). The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space. Journal of transport geography, 97, 103215. https://doi.org/10.1016/j.jtrangeo.2021.103215
  • Li, S., Yang, H., Zhang, G., Ling, Z., Xiong, Y., & Li, Y. (2019, July). What is the best catchment area of a metro station? A study based on station level ridership modeling. In 2019 5th International Conference on Transportation Information and Safety (ICTIS) (pp. 1239-1244). IEEE. https://doi.org/10.1109/ICTIS.2019.8883789
  • El-Geneidy, A., Grimsrud, M., Wasfi, R., Tétreault, P., & Surprenant-Legault, J. (2014). New evidence on walking distances to transit stops: Identifying redundancies and gaps using variable service areas. Transportation, 41, 193-210. https://doi.org/10.1007/s11116-013-9508-z
  • O'Sullivan, S., & Morrall, J. (1996). Walking distances to and from light-rail transit stations. Transportation Research Record, 1538(1), 19-26.
  • Kim, T., Sohn, D. W., & Choo, S. (2017). An analysis of the relationship between pedestrian traffic volumes and built environment around metro stations in Seoul. KSCE Journal of Civil Engineering, 21, 1443-1452. https://doi.org/10.1007/s12205-016-0915-5
  • Pekdemir, M. I., Altintasi, O., & Ozen, M. (2024). Assessing the Impact of Public Transportation, Bicycle Infrastructure, and Land Use Parameters on a Small-Scale Bike-Sharing System: A Case Study of Izmir, Türkiye. Sustainable Cities and Society, 101, 105085. https://doi.org/10.1016/j.scs.2023.105085
  • Maas, S., Attard, M., & Caruana, M. A. (2020). Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria. Transportation Research Part A: Policy and Practice, 140, 81-97. https://doi.org/10.1016/j.tra.2020.08.003
  • Wu, Y., Li, W., Yu, Q., & Li, J. (2022). Analysis of the Relationship between Dockless Bicycle‐Sharing and the Metro: Connection, Competition, and Complementation. Journal of Advanced Transportation, 2022(1), 5664004. https://doi.org/10.1155/2022/5664004
  • Tresidder, M. (2005). Using GIS to measure connectivity: An exploration of issues. Portland State University: Field Area Paper, 1-43.
  • Zacharias, J., & Zhao, Q. (2018). Local environmental factors in walking distance at metro stations. Public Transport, 10, 91-106. https://doi.org/10.1007/s12469-017-0174-y
  • Gan, Z., Yang, M., Feng, T., & Timmermans, H. J. (2020). Examining the relationship between built environment and metro ridership at station-to-station level. Transportation Research Part D: Transport and Environment, 82, 102332. https://doi.org/10.1016/j.trd.2020.102332
  • Sun, G., Zacharias, J., Ma, B., & Oreskovic, N. M. (2016). How do metro stations integrate with walking environments? Results from walking access within three types of built environment in Beijing. Cities, 56, 91-98. https://doi.org/10.1016/j.cities.2016.03.001
  • Zhao, J., Deng, W., Song, Y., & Zhu, Y. (2013). What influences Metro station ridership in China? Insights from Nanjing. Cities, 35, 114-124. https://doi.org/10.1016/j.cities.2013.07.002
  • Dill, J. (2004). Measuring network connectivity for bicycling and walking. In 83rd annual meeting of the Transportation Research Board, Washington, DC (pp. 11-15).
There are 22 citations in total.

Details

Primary Language English
Subjects Transportation Engineering
Journal Section Research Articles
Authors

Oruç Altıntaşı 0000-0002-4217-1890

Alper Kundakci 0009-0002-7009-958X

Publication Date July 31, 2024
Submission Date June 14, 2024
Acceptance Date July 26, 2024
Published in Issue Year 2024 Volume: 5 Issue: 1

Cite

APA Altıntaşı, O., & Kundakci, A. (2024). Investigation of the road network structure around rail transit stations. Journal of Innovative Transportation, 5(1), 17-21. https://doi.org/10.53635/jit.1501395