Open data-based urban models: An assessment for Canadian cities

Abstract

Digital urban models are a rapidly advancing area of study in urban design and policymaking. Many cities have adopted this technology, yielding promising results in developing localized models. However, there are only a limited number of recent Canadian examples, partly due to the high costs of model construction and maintenance. Canadian cities continue to face numerous challenges even when utilizing open data and software. To democratize open data-driven urban model development in Canada, we must understand the current open data landscape and explore how available open data and software can support urban model building. This paper thus reviews the Canadian open-source data landscape in comparison with world-leading cities, highlighting how model feasibility and maturity hinge on the quality and availability of accessible datasets. We then demonstrate the creation of a city-wide, spatially explicit urban model for the City of Winnipeg, Canada, using only open-source datasets and software. The findings of this research lay the groundwork for adoption in cities with similar data limitations and can inform urban planners, policymakers, and researchers about the feasibility of leveraging open data-based urban models for data-driven decision making.