Analysis of Potential High-Speed Rail Routes: A Case of GIS-Based Multicriteria Evaluation in Turkey
Publication: Journal of Urban Planning and Development
Volume 147, Issue 2
Abstract
All over the world, governments, policy makers, and practitioners are searching for proper routes and corridors to invest transportation infrastructures such as new railways, highways, and multimodal ways. Although it is one of the important steps of development, finding a suitable route for new transport infrastructure is a complicated and conflicting task for of various reasons. Possible social and environmental impacts on society and increasing cost and technical pressures on decision makers are some of these reasons. Taking into consideration aspects of different evaluation criteria, a geographic information system (GIS)-based multicriteria solution approach is proposed in this study. Potential high-speed rail (HSR) routes in Turkey are considered as a case study. After gathering and processing the related GIS data, weights are assigned to each criterion by using the fuzzy analytic hierarchy process in order to indicate their relative importance. Then, the additive ratio assessment method is applied to carry out the multicriteria (13 technical, social, and demographic criteria) evaluation and selection of the suitable alternatives (among 20 HSR routes) under given circumstances. It was found that the corridor from the west part of Turkey (from İzmir and Manisa) to the Marmara region (Kocaeli and İstanbul) had the highest priority, followed by the corridor from Ankara to Kayseri. HSR trains could potentially reduce the journey times to Kocaeli and İstanbul from İzmir and Manisa, as compared with driving, by 46% and 45%, respectively. The results of this study can be used to evaluate potential HSR corridors/routes or similar transport infrastructures in other countries.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Data that are available upon request are pairwise matrix of experts and criteria values.
Acknowledgments
The authors thank the two anonymous reviewers and the editor for useful comments that have led to an improvement in the paper.
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Received: Jul 26, 2020
Accepted: Nov 17, 2020
Published online: Feb 25, 2021
Published in print: Jun 1, 2021
Discussion open until: Jul 25, 2021
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