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Evaluating transport externalities of urban growth: a critical review of scenario-based planning methods

  • S. Perveen
  • T. YigitcanlarEmail author
  • Md. Kamruzzaman
  • J. Hayes
Review

Abstract

Urban growth is an important phenomenon, which is taking place on an unprecedented scale, and its impacts on society and the environment are evident. In theory, an evaluation of such urban growth through scenario-based planning helps planners to better assess the future impacts of growth and develop better policies and plans. Within this context, the assessment of transport impacts is particularly important as transport plays an important role in shaping urban growth. Additionally, transport sector alone is responsible for about one-third of the greenhouse gas emissions of cities, which has detrimental effects on the environment, economy, community health, and quality of life. In practice, however, scarce evidence exists outlining the challenges of scenario-based evaluation and how to best address these while modelling the transport impacts of various urban growth scenarios. This research addresses these gaps in the literature and assesses the effectiveness of scenario-based planning methods that are used for modelling the transport impacts of alternative urban growth scenarios. The methodological approach of the study consists of a critical review of the key literature and relevant methods that are commonly used to assess transport impacts. The results of this analysis highlight limitations of existing methods for effectively evaluating transport externalities of urban growth scenarios. The findings suggest that among many reviewed models, the ILUTE, URBANSIM and TRANUS simulation models are identified as significant ones. However, due to various limitations of the former two, TRANUS is noted as the most suitable one for evaluating the transport impacts of urban growth scenarios.

Keywords

Urban growth scenarios Integrated land use and transportation models Environmental impact Assessment methods Scenario evaluation Scenario generation 

Notes

Acknowledgments

This research is conducted with funding support from the Australian Postgraduate Award provided jointly by the Australian Federal Government and the Queensland University of Technology. Authors are grateful for the constructive comments of the editor and anonymous referees on an earlier version of this paper.

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Copyright information

© Islamic Azad University (IAU) 2016

Authors and Affiliations

  1. 1.School of Civil Engineering and Built Environment, Science and Engineering FacultyQueensland University of Technology (QUT)BrisbaneAustralia

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