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Dr. Alessia Calafiore
Dr. Rafael H. M. Pereira
Spatial Data Science for Sustainable and Inclusive Cities
Abstract: In this presentation, I will give an overview of my research at the intersection of spatial data science, urban analytics and accessibility, and sustainable mobility. Specifically, I will showcase work related to the development of open data science tools and methods for transportation network modeling used to examine spatial accessibility, energy use and the environmental performance of urban mobility systems. These tools contribute to research and planning by aiding researchers, students, and practitioners in effectively handling large-scale geospatial data for the examination of urban transportation networks and mobility futures. I will give particular attention to two projects related to: (1) a new scalable computational model to estimate public transport emissions at high spatial and temporal resolutions; and (2) recent developments of powerful multimodal routing models and their contribution to the analysis of socioeconomic and spatial inequalities in access to opportunities. At the end, I will discuss some of the advantages and limitations of these tools and models, reflecting on new research avenues for using spatial data science for sustainable and inclusive cities.
Bio: Rafael H. M. Pereira is a senior researcher in the fields of urban analytics, spatial data science and transport studies at the Institute for Applied Economic Research (Ipea), Brazil, where he leads the Data Science team. His research looks broadly at how urban policies and technologies shape the spatial organization of cities, human mobility as well as their impacts on social and health inequalities. Some of his key contributions to the fields of urban analytics and planning involve the development of new methods and open-source computational tools to the study of urban systems and transportation networks. These contributions emerge from substantive interests around social justice and sustainability issues in urban development, with particular focus on transportation equity and inequalities in access to opportunities, and the environmental impacts of built environments and mobility patterns. With a background in Sociology and Demography, Dr. Pereira obtained his PhD in Geography from the Transport Studies Unit at Oxford University.
Dr. Somayeh Dodge
Data-driven Movement Analysis for Understanding Human Behavior and Interaction in Changing Urban Environments
Abstract: Data-driven movement analysis plays a crucial role in understanding urban dynamics and human exposure and access to built and social environments. The increasing environmental variability arising from climate change-induced events, including natural disasters, can cause substantial shifts in human movement activity and their daily interactions. Investigating these patterns can inform sustainability planning efforts to enhance human well-being, increase communities' resilience, and reduce inequalities in accessing urban resources. Using movement as a marker of behavior, this presentation explore various applications of movement analysis in investigating individuals' behavioral responses to environmental changes and their social interactions.
Bio: Somayeh Dodge is an Associate Professor of Spatial Data Science in the Department of Geography at the University of California, Santa Barbara. She serves on the Board of Directors of the University Consortium for Geographic Information (UCGIS). She is currently a Senior Fellow of the ETH/UZH Collegium Helveticum program and a Fellow of the University of Zurich Digital Society Initiative (DSI). She received her PhD in Geography with a specialization in Geographic Information Science (GIScience) from the University of Zurich, Switzerland in 2011. She is a recipient of the 2021 CAREER award from the U.S. Science National Foundation (NSF), and the 2022 Emerging Scholar Award of the Spatial Analysis and Modeling Specialty Group of the American Associations of Geographers (AAG). Somayeh's research focuses on developing data analytics, knowledge discovery, modeling, and visualization techniques to study movement behavior in dynamic human and ecological systems.
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