Smart Specialization and Resilience
All sessions will be held virtually by Zoom
Ms Zhiying LI PhD Candidate, Department of Geography, The Ohio State University, Columbus, Ohio, USA
Zhiying Li is a Ph.D. candidate at the Department of Geography at The Ohio State University. Her research interests are hydro-climatology, applied climatology, and environmental data science. Her research focuses on investigating the water cycle from local to continental scale in a changing climate using multi-source observations. She is also interested in climate change implications on multiple sectors such as utility management and agriculture. Zhiying’s doctoral dissertation was funded by a National Science Foundation Doctoral Dissertation Research Improvement Grant. Zhiying has published in leading journals such as Earth-Science Reviews, Geomorphology, Anthropocene, and Energy. She has served as a manuscript reviewer for Physical Geography and Utilities Policy and a book reviewer for Elsevier. She has won numerous awards and fellowships for her research and presentation skills, such as the Presidential Fellowship at OSU, the Best Oral Presentation at the East Lakes Division of the American Association of Geographers, and the American Meteorological Society Annual Meeting Matthew J. Parker Travel Grant.
Before joining OSU, Zhiying received her master’s degree in Physical Geography at the Institute of Geographic Sciences and Natural Resources Research at the University of Chinese Academy of Sciences in China in 2017, and a bachelor’s degree in Soil and Water Conservation at Northwest A&F University in China in 2014. Her master’s research focuses on modeling the impacts of climate change and land-use change on watershed runoff and sediment yield.
Data science in geography: from hydrology to applied climatology
Climate change and human activities have changed long-term hydrological processes. Such changes are expected to continue in the future and pose a management challenge. At the same time, data science methods are increasingly important in geography and environmental science. The emerging large quantities of data change the ways scientists do research and allow them to address environmental problems in a new way. My research utilizes hydrological and climate models, machine learning, spatial analysis, and multiscale observations to inform water resources management. The climate change challenges as applied in the utility sector are also discussed. This seminar highlights two data science applications in hydrology and climatology. First, coupling hydrological framework, climate models, and geospatial data, I investigated the relative importance of drivers on streamflow changes over space and time in the continental United States in six decades from 1950 to 2009. Second, I addressed the short-term utility management challenge due to the increasing use of clean energy in a changing climate using machine learning algorithms. Overall, it is critical to use data science methods to understand hydrological change and provide implications to climate-sensitive sectors to better adapt to a changing environment.
Dr Hyunuk KIM Postdoctoral Associate, Information Systems, Questorm School of Business, Boston, MA, USA
Dr Hyunuk Kim is a computational social scientist exploring how individuals process information and collectively shape knowledge, culture, and market in space. He uses network science, natural language processing, and machine learning methods to identify latent factors of collaboration, business behaviors, and the spread of misinformation. He currently works as a Postdoctoral Associate in the Information Systems Department at Boston University’s Questrom School of Business, after receiving a doctoral degree in Industrial and Management Engineering from Pohang University of Science and Technology.
Data-driven representations of scientific specialization and urban resilience
Human societies build on interactions of people, communities, and markets. These interactions are structured at various scales, ranging from cities to continents, and act as channels where information and infectious diseases spread. Understanding the complex relationship between geography and human behaviors is increasingly important to design smart, resilient, and resource-efficient systems in the digital and pandemic era. Over the past decades, computational tools have been applied to large-scale data for taming socio-spatial complexity. Beyond summarizing observational patterns, computational studies infer characteristics of agents, reveal mechanisms of social dynamics in space, and suggest models for testing scenarios. My research presented in this seminar incorporates these schemes with machine learning and network science methods and quantifies 1) comparative advantages within a scientific discipline and 2) accommodation booking behaviors along the hierarchy of urban areas. Specifically, I estimate national specialization on a reconstructed knowledge structure of nuclear fusion research and measure the extent to which complementarity affects international collaboration. In addition, using customer-level booking data from a Korean accommodation platform, I map location trajectories of individual users onto urban hotspots and then compare customer behaviors before and after the COVID-19 outbreak to provide insights into urban resilience. I will conclude this talk with the geographical implications of data-driven approaches for smart specialization and resilience.
Professor Adolf Koi Yu NG Professor, Department of Supply Chain Management, Asper School of Business, University of Manitoba, Winnipeg, Canada
Obtained his DPhil from the School of Geography and the Environment of the University of Oxford (UK), Adolf Ng excels in the research and teaching of sustainable transport and supply chains, climate adaptation and resilience (A&R) planning and management of transport and urban infrastructures, environmental and socio-economic impacts of infrastructures on city and regional development, transport systems and regional integration. Securing more than HKD 50 million competitive research grants, his scholarly outputs include seven books, more than 80 papers in leading journals, and other forms of publications. He receives numerous prestigious accolades, for instance, the Fulbright Scholar Program (US), Endeavour Research Fellowship (Australia), University of Manitoba’s Rh Award for Outstanding Contributions to Scholarship and Research in Interdisciplinary Studies (Canada), IAME’s Eagle Prize for Outstanding Young Scholar in Maritime Research, and Best Paper Awards in ISI journals (e.g., Maritime Policy & Management). With such expertise, he frequently offers strategic advice to major organizations, for instance, United Nations (UN), European Commission (EC), and the Climate Bonds Initiatives (CBI). Also, he serves as a member for the selection committees of the Social Science and Humanities Research Council of Canada (SSHRC)’s competitive grants and postdoctoral fellowship selection. He is currently an Associate Editor of Maritime Policy & Management (IF: 3.000) and The Asian Journal of Shipping and Logistics, and an editorial board member of reputable international scholarly journals (e.g., Journal of Transport Geography, Transportation Research Part D: Transport and Environment, Ocean and Coastal Management).
The Socio-Economic Impacts of Arctic Shipping and the Resilience of Local Communities in the Canadian Arctic Region
As the rate of ice melt in the Arctic region increases, the potential for shipping activities is also increasing. Infrastructure along the Northwest Passage (NWP) in Canada’s Arctic is almost non-existent. This presents major challenges to any response efforts in the case of a natural disaster. Also, the Arctic is home to many indigenous communities. Consequently, it is of vital importance to protect the livelihood of the rights holders in this area and the Arctic marine environment. Thus, it is necessary to assess the potential risk of pollutants arising from increased shipping activity in both the short- and long-terms. Understanding such, based on the expert elicitation from the public, private, academic sectors, as well as the local indigenous communities, this project develops a decision-making model based on the Bayesian theory that assesses the impacts of a ship’s oil spill on local communities in the Canadian Arctic in a multi-period. The results highlight the potential serious socio-economic consequences of shipping activities on local livelihood and the need for stronger collaborations between the government, private sectors, and the local, indigenous population in the long term.
Mr Patrick ADLER PhD Candidate, Urban Planning, UCLA, Los Angeles, California, USA
Patrick Adler is a graduating PhD Student at UCLA’s Luskin School and Research Associate at the University of Toronto’s School of Cities. His research revolves around the themes of regional economic development, localized innovation, and urban evolution.
Gatekeeping the Turnstile: The Geography of Music Festival Selection
The demand for curation functions is growing in advanced economies. Curators support the operation of creative industries by choosing among symbolically-differentiated products or facilitating such choices. They include buyers, reviewers, selectors, professional critics, and automated tools in areas as diverse as entertainment, high-technology, and finance. This paper investigates the intuition that the highly asymmetrical geographies of creative value-added result from agglomeration economies to curation. It proposes several channels through which creative producers and curators would benefit from co-location and investigates this theory through a case study from the US music industry.
The study analyzes 77,652 appearances at major US festivals between 2017 and 2019 to establish regional trading flows between music festivals (importers) and music scenes (exporters). The geography of music exporters is shown to be highly concentrated with only 4 metropolitan areas exporting nearly 40% of all acts. This geography of music production is shown to be related to a broader geography of curation. Acts selected to music festivals are, controlling for popularity, more likely to have been selected to other music festivals, more likely to be drawn from the festival programmer’s environment and more likely to be drawn from areas with recognizable ‘place brands’. These results are interpreted as evidence of curation-type localization benefits.
All are welcome!
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