Abstract

This paper develops a scenario analysis and visualization tool for an Integrated Transport, Land-Use and Energy (iTLE) model to spatially analyze and predict changes in transport and land-use environment. The decision support tool operates by taking the iTLE model output data as input which includes residential location of households, individuals’ characteristics, and vehicle fleet information. Use of the tool is showcased through a scenario analysis of a ‘business as usual (BAU)’ projection versus a ‘COVID-19 pandemic scenario’ for Halifax, Canada. Agent-based microsimulation explores the possible future changes in households’ socio-demographic characteristics and travel behaviour in the post-pandemic time. Forecasting up to the year 2025 and comparing between BAU and pandemic scenario shows that, many of the lower median income areas in the BAU projection are estimated to have a much lower median income under the COVID-19 scenario. Furthermore, the COVID-19 scenario only slightly decreases the proportion of the overall population with a transit pass. Under the pandemic scenario, the percentage of households with three or more cars experiences significant growth in urban and suburban areas. Outcomes of this study will offer policymakers a greater understanding of the transformation pattern of urban and suburban neighborhoods in the post-pandemic period. The developed iTLE VIZ tool will allow planners to formulate complex transport and land-use scenarios and simulate them for examining urban systems transformation.

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