Urban Data Science for Sustainable Mobility

Transportation is a major sector of human activity fueling the climate crisis. Therefore, there is an urgent need to make mobility more sustainable. Due to contemporary urbanization, this need is particularly pressing within cities, and can be addressed through the emerging interdisciplinary field of Urban Data Science. This field combines methods from Data Science with domain knowledge of the city, making use of the increasing availability and volume of data on urban environments.

In the realm of mobility, sustainability is gaining popularity as a framework for research and policy-making. Nevertheless, available data, tools, and research efforts for sustainable transportation modes like cycling are still dwarfed by those for motorized modes, constituting a considerable research gap. In addition, techno-optimist approaches to sustainability, such as the excessive support
for car-centric motorized transportation systems, entail serious ethical pitfalls. To address these challenges, this thesis explores how Urban Data Science can ethically support human mobility that is both environmentally and socially sustainable, through the two lenses of Data and Networks.

In the realm of Data, we develop an algorithm for multi-purpose spatial network simplification, and a data quality assessment pipeline tailored specifically to bicycle networks. Further, we outline pathways for incorporating data ethics into computational approaches to spatial manifestations of social inequalities. In the realm of Networks, we develop data-driven methods for the planning of bicycle networks and low-traffic neighbourhoods, and showcase their application to various cities.
Lastly, we investigate the impact of transportation infrastructure on social connections in cities, quantitatively corroborating that urban highways are barriers to social ties.

Stemming from various interdisciplinary collaborations, the results of this thesis cover multiple conceptual levels of Urban Data Science, from open source software development and data quality assessment to transportation network planning and the intersection of social and spatial networks. Through these efforts, this thesis advances the emerging field of Urban Data Science, showcasing the field’s potential to make human mobility more sustainable.