Please note that the RPG Seminar Series will be held virtually via Zoom on 17 June 2021 (Thursday), 13:00 pm
Please be ready 5 minutes prior to the scheduled time.
High-quality window views are appreciated for human’s physical and psychological wellbeing, aesthetic enjoyment, and property values; yet, such views cannot be accessed equally particularly in high-rise high-density cities like Hong Kong. A holistic assessment of window views, which examines the community’s equality of possessing the scenic landscape, is thus vital to sustainable urban development. This study proposes an urban computing approach, consisting of (i) a hierarchy of window view characteristics (HoWViCi), (ii) city information model (CIM)-based window view reconstruction, (iii) machine learning-based assessment, and (iv) adaptive view index service, for quantifying city-scale window views for smart city applications. The theoretical advancement in this study can bridge the gap between the spatial big data in CIM and underexploited window view assessment for GISciences and related disciplines; the findings and practical toolkits may also contribute to sustainable town planning and real estate development for urban dwellers.
Keyword: Urban computing; window view; automatic assessment; city information model; GISciences; urban planning; high-rise high-density city.
About the Speaker
Mr. Maosu LI is a second-year Ph.D. student in the Department of Urban Planning and Design at the University of Hong Kong. He obtained his Bachelor’s degree in Geodesy and Geomatics Engineering from Southwest Jiaotong University. His research interest includes City Information Modelling, urban computing, and spatiotemporal big data retrieval. Currently, he is working on the understanding and computing of 3D window views for sustainable urban planning and real estate development in Hong Kong.
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Enquiries: 3917 2721
Department of Urban Planning and Design
THE UNIVERSITY OF HONG KONG