Evaluating future railway-induced urban growth of twelve cities using multiple SLEUTH models with open-source geospatial inputs

Document Type

Journal Article

Publication Date

2023

Subject Area

land use - impacts, land use - planning, mode - rail, place - urban, planning - methods, technology - geographic information systems

Keywords

Urban growth, train station

Abstract

Plausible urban growth projections aid in the understanding and treatment of multidisciplinary issues faced in society. In this work, we investigated the possible effects of train stations on urban growth by comparing urban projections from a cellular-automata-based land use change model, named SLEUTH, with versions (i.e. SLEUTsH and SLEUTsHGA introduced in this study) that can consider railway-induced urban growth and those (i.e. SLEUTH and SLEUTHGA) that do not. It was found that the influence of the railway stations on urban growth varied with time and according to each city. In general, railway stations induced urbanization in their immediate surroundings. However, edge growth, which is growth at the urban boundaries was slow in the first five years of the future prediction. As demonstrated by the higher urban growth rates simulated for the first few years in the SLEUTsH cases than the SLEUTH cases, the presence of railway stations will lead to more rapid urbanization in the 2040s. Mainly relying on publicly available GIS datasets, this work demonstrates the potential for modeling railway-induced urban growth on a global scale. The findings can be further confirmed with other cellular-automata models using a similar methodology.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

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http://www.sciencedirect.com/science/journal/22106707

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