Beyond Spatial Proximity: Integrating GIS and User Perceptions to Assess Public Transport Accessibility in Indonesian Medium-Sized Cities
DOI:
https://doi.org/10.61978/logistica.v4i2.1741Keywords:
public transport accessibility, Geographic Information System, perceived accessibility, walkability, qualitative multiple-case study, sustainable urban mobility, Indonesian medium-sized citiesAbstract
Public transport accessibility is fundamental to sustainable urban mobility, yet conventional GIS-based spatial indicators often fail to capture commuters' lived experiences. This study integrates GIS-based and perception-based accessibility measures to provide a more comprehensive understanding of conditions in Indonesian medium-sized cities. A qualitative multiple-case study design was conducted across four cities—Malang, Mataram, Pontianak, and Kendari—involving fourteen informants including commuters, operators, planners, elderly passengers, and a person with disability. Data were gathered through semi-structured interviews, field observations, document review, and spatial analysis, then analyzed using open, axial, and selective coding alongside cross-case comparison, integrating spatial and qualitative findings. Results reveal that objective spatial accessibility and perceived accessibility are often inconsistent, producing four typologies combining high/low spatial and perceived accessibility. Key factors shaping perceived accessibility include walkability, sidewalk continuity, pedestrian safety, service reliability, waiting time, route suitability, information availability, intermodal integration, and inclusive infrastructure. Some residents near transit stops reported poor accessibility due to discontinuous pedestrian infrastructure and unreliable services, while others accepted longer walking distances when services were predictable and affordable—showing accessibility depends on the entire travel experience, not just spatial proximity. The study concludes that GIS indicators should be complemented by perception-based measures, offering an integrated framework to identify mismatches between infrastructure and commuter experience and support inclusive, user-centered transport planning in Indonesian medium-sized cities.
References
Alkhereibi, A. H., Wakjira, T. G., Küçükvar, M., & Onat, N. C. (2023). Predictive Machine Learning Algorithms for Metro Ridership Based on Urban Land Use Policies in Support of Transit-Oriented Development. Sustainability, 15(2), 1718. https://doi.org/10.3390/su15021718 DOI: https://doi.org/10.3390/su15021718
Ann, S., Jiang, M., & Yamamoto, T. (2019). Re-Examination of the Standards for Transit Oriented Development Influence Zones in India. Journal of Transport and Land Use, 12(1). https://doi.org/10.5198/jtlu.2019.1534 DOI: https://doi.org/10.5198/jtlu.2019.1534
Beck, L. C., & Oktay, S. Ö. (2023). Designing a Cycling Dashboard as a Way of Communicating Local Sustainability. Sustainability, 15(17), 12829. https://doi.org/10.3390/su151712829 DOI: https://doi.org/10.3390/su151712829
Brodeur-Ouimet, P., & Cloutier, M. (2024). Walkable and Safe Route to Transit for Pedestrians in Greater Montréal: An Environmental Justice Approach. Transportation Research Record Journal of the Transportation Research Board, 2678(9), 562–573. https://doi.org/10.1177/03611981241230309 DOI: https://doi.org/10.1177/03611981241230309
Cadiz, N. R. R., Mariano, K. L. S., Dumalag, J. B. L. C., Retamar, A. E., & Aceron, J. C. F. (2023). Information, Education, and Communication Campaign in the Philippines: Capacitating Academic Institutions and Government Agencies using Geographic Information System, Radar Remote Sensing, and Artificial Intelligence. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003874751&partnerID=40&md5=f2fc4df1e093e75454c803c7f2ce8ad7
Cartenì, A., & Henke, I. (2022). Transportation Planning, Mobility Habits and Sustainable Development in the Era of COVID-19 Pandemic. Sustainability, 14(5), 2968. https://doi.org/10.3390/su14052968 DOI: https://doi.org/10.3390/su14052968
Chidambara, & Gupta, S. (2018). Effect of Walkability on Users Choice of “Walking” the Last Mile to Transit Stations: A Case of Delhi Metro. Urban Studies and Public Administration, 1(1), 1. https://doi.org/10.22158/uspa.v1n1p1 DOI: https://doi.org/10.22158/uspa.v1n1p1
Choosakun, A., & Yeom, C. (2021). Developing Evaluation Framework for Intelligent Transport System on Public Transportation in Bangkok Metropolitan Regions Using Fuzzy AHP. Infrastructures, 6(12), 182. https://doi.org/10.3390/infrastructures6120182 DOI: https://doi.org/10.3390/infrastructures6120182
Clifton, K. J. (2019). Transferability &Amp; Forecasting of the Pedestrian Index of the Environment (PIE) for Modeling Applications. https://doi.org/10.15760/trec.218 DOI: https://doi.org/10.15760/trec.218
Darmawan, C. N., I’zzuddiin, M., & Alina, A. N. (2023). Analysis of Public Green Open Space (RTH) Distribution Using Geographic Information System (GIS) Methods in the Districts of Sumenep City. Journal of Geospatial, Remote Sensing, and Survey, 1(1), 7–16.
Fillone, A. M., & Mateo‐Babiano, I. (2018). Do I Walk or Ride the Rickshaw? Examining the Factors Affecting First- And Last-Mile Trip Options in the Historic District of Manila (Philippines). Journal of Transport and Land Use, 11(1). https://doi.org/10.5198/jtlu.2018.1077 DOI: https://doi.org/10.5198/jtlu.2018.1077
Hamidi, S., & Moazzeni, S. (2019). Examining the Relationship Between Urban Design Qualities and Walking Behavior: Empirical Evidence From Dallas, TX. Sustainability, 11(10), 2720. https://doi.org/10.3390/su11102720 DOI: https://doi.org/10.3390/su11102720
Harumain, Y. A. S., Azmi, N. F., & Yusoff, S. (2021). Assessing Elements of Walkability in Women’s Mobility. Journal of the Society of Automotive Engineers Malaysia, 1(3), 208–215. https://doi.org/10.56381/jsaem.v1i3.61 DOI: https://doi.org/10.56381/jsaem.v1i3.61
Horita, F. E. A., Albuquerque, J. P. D., Degrossi, L. C., Mendiondo, E. M., & Ueyama, J. (2015). Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks. Computers and Geosciences, 80, 84–94. https://doi.org/10.1016/j.cageo.2015.04.001 DOI: https://doi.org/10.1016/j.cageo.2015.04.001
Jamaleddin, M., Ibrahim, H., Ferwati, M. S., Khamidi, M. F., & Indraganti, M. (2022). Pre-Transit Oriented Development Assessment Guidelines for Assessing Metro Station Dependent Component Area. Designs, 6(3), 56. https://doi.org/10.3390/designs6030056 DOI: https://doi.org/10.3390/designs6030056
Jeong, I., Choi, M., Kwak, J., Ku, D., & Lee, S. (2023). A Comprehensive Walkability Evaluation System for Promoting Environmental Benefits. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-43261-0 DOI: https://doi.org/10.1038/s41598-023-43261-0
Moini, N. (2015). Development of an Analytical Framework to Rank Pedestrian and Cyclist Projects. https://doi.org/10.5038/cutr-nctr-rr-2015-03 DOI: https://doi.org/10.5038/CUTR-NCTR-RR-2015-03
Nasri, A., Younes, H., & Zhang, L. (2020). Analysis of the Effect of Multi-Level Urban Form on Bikeshare Demand: Evidence From Seven Large Metropolitan Areas in the United States. Journal of Transport and Land Use, 13(1). https://doi.org/10.5198/jtlu.2020.1615 DOI: https://doi.org/10.5198/jtlu.2020.1615
Salter, B., & Alexander, S. (2022). Getting There: The Effect of First and Last Mile Infrastructure and Services on Rail Ridership. Transportation Research Record Journal of the Transportation Research Board, 2676(10), 402–412. https://doi.org/10.1177/03611981221089543 DOI: https://doi.org/10.1177/03611981221089543
Schlossberg, M., Meyer, C., Dill, J., & Ma, L. (2013). Measuring the Performance of Transit Relative to Livability. https://doi.org/10.15760/trec.135 DOI: https://doi.org/10.15760/trec.135
Shen, Z., Li, J., Zhou, S., Li, M., Chen, Y., Jiang, Y., & Xue, X. (2017). Weakly Supervised Dense Video Captioning. 5159–5167. https://doi.org/10.1109/cvpr.2017.548 DOI: https://doi.org/10.1109/CVPR.2017.548
Silva, D. C. d., King, D. A., & Lemar, S. V. (2019). Accessibility in Practice: 20-Minute City as a Sustainability Planning Goal. Sustainability, 12(1), 129. https://doi.org/10.3390/su12010129 DOI: https://doi.org/10.3390/su12010129
Sugihara, R., Ikaruga, S., Tsuboi, S., Kobayashi, T., Song, J., & Zhao, S. (2018). Proposal of a Support System for Formulating Compact City Planning Based on the City Planning of Portland. Journal of Architecture and Planning (Transactions of Aij), 83(749), 1251–1261. https://doi.org/10.3130/aija.83.1251 DOI: https://doi.org/10.3130/aija.83.1251
Thakur, D., & Walia, A. (2024). Strategies and Implications That Can Be Used to Improve Walkability Through Urban Design. Interantional Journal of Scientific Research in Engineering and Management, 08(03), 1–5. https://doi.org/10.55041/ijsrem29328 DOI: https://doi.org/10.55041/IJSREM29328
Tzouras, P. G., Mitropoulos, L., Koliou, K., Stavropoulou, E., Karolemeas, C., Antoniou, E., Karaloulis, A., Mitropoulos, K., Vlahogianni, E. I., & Κεπαπτσόγλου, Κ. (2023). Describing Micro-Mobility First/Last-Mile Routing Behavior in Urban Road Networks Through a Novel Modeling Approach. Sustainability, 15(4), 3095. https://doi.org/10.3390/su15043095 DOI: https://doi.org/10.3390/su15043095
Venter, C. (2020). Measuring the Quality of the First/Last Mile Connection to Public Transport. Research in Transportation Economics, 83, 100949. https://doi.org/10.1016/j.retrec.2020.100949 DOI: https://doi.org/10.1016/j.retrec.2020.100949
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Logistica : Journal of Logistic and Transportation
This work is licensed under a Creative Commons Attribution 4.0 International License.
