Movement Analytics for Sustainable Mobility
Contemporary humanity enjoys mobility levels that are unprecedented in history. While this has benefits, it also has enormous social, health, and environmental costs. Mitigating these costs and making transportation more equitable and effective is crucial if civilization is to survive the twenty-first century—a world that will see 9 billion people, most of whom will crowd into cities. This lecture will describe the concept of sustainable mobility and how new, data-driven science allows scholars and practitioners to address these essential issues. Harvey J. Miller will provide examples from his research and projects from the Center for Urban and Regional Analysis (CURA) at Ohio State University that illustrate ways to leverage these new data sources to gain insights into mobility dynamics and their implications for urban sustainability.
Harvey J. Miller is the Bob and Mary Reusche Chair in Geographic Information Science, director of the Center for Urban and Regional Analysis, and professor in the Department of Geography at the Ohio State University in Columbus, Ohio. Miller also is a courtesy professor in the Department of City and Regional Planning, a member of the Faculty Advisory Board of the Sustainability Institute and an Affiliated Faculty of the Translational Data Analytics Institute at Ohio State, as well as the chair of the Mapping Science Committee of the U.S. National Academies. Miller's research and teaching focus on the intersection between geographic information science and transportation science. He wants to understand how people use mobility and communications technologies to allocate scarce time among activities in geographic space—a perspective known as time geography. He is also interested in the social dimensions of transportation, the relationships between mobility and public health, and data-driven urban science to support livable and sustainable communities. His main approach to questions of mobility, livability, and sustainability is the development and application of GIS and spatial analysis techniques to extract information from fine-grained mobility and spatio-temporal data.Watch Online