Zoom: https://illinois.zoom.us/j/85784639803?pwd=Y6IWiAVIKRTLFamXaEcgapeuIKnTva.1
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Abstract:
COVID-19 has significantly affected the behavioural patterns of urban visitors. However, the non-linear relationships between visitor behaviour and built environments, particularly how these relationships have evolved during the pandemic, have not yet been extensively studied. Using over 10 million mobile big data records collected over three years in Fukuoka, Japan, incorporating the XGBoost machine learning model and SHAP-PDP interpretation method, we identified non-linear relationships between visitor behaviours and built environments. Our findings uncovered significant non-linear impacts on visitor behaviour of several urban characteristics, such as floor area ratio, building coverage ratio, road density, and POI richness.
Bio:
Kojiro Sho received his Ph.D. in urban engineering from the Department of Urban Engineering, the University of Tokyo in 2017. He is currently an associate professor at the International Development & Regional Planning Unit, the Department of Urban Engineering, the University of Tokyo. He has a broad interest in spatial analysis using big data. By clarifying the dynamics between human activities and urban land use, his research interests mainly cover gentrification, spatial inequality issues in Ease Asian and Global South countries.
Part of the Siebel School Speakers Series. Faculty Host: Han Zhao
Meeting ID: 857 8463 9803
Passcode: csillinois
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