Our winter quarter seminar series continues February 27, 12:30-1:30pm in Gould 440. This is an in-person seminar.
Title:
Utilizing Time Series Street View Imagery to Assess Visual Perceptual Quality in Urban Neighborhoods: A Case Study of New York City and Singapore
Abstract:
Discover an innovative method using time series street view imagery to evaluate urban neighborhoods’ visual quality. This approach, differing from traditional survey methods, employs deep learning on a decade-long dataset, analyzing six perception indicators in diverse geographies. Our case studies in Singapore and New York City public housing demonstrates that temporal imagery can effectively assess spatial equity and monitor the visual environmental qualities of neighborhoods over time, providing a new, comprehensive, and scalable workflow. It can help governments improve policies and make informed decisions on enhancing the design and living standards of urban residential areas. Join us to see how this cutting-edge technique is transforming urban analysis and policy development.
Related Paper:
Wang, Z., Ito, K., & Biljecki, F. (2024). Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery. Cities, 145, 104704. Available at ResearchGate.
Bio:
Zeyu Wang is a PhD student in the interdisciplinary UDP program at the University of Washington. Holding a Bachelor of Science in Geography and a Master of Urban Planning (MUP), his academic pursuits are deeply rooted in understanding built environment and human mobility patterns, with a strong focus on urban data science. He is passionate about using advanced technologies and novel data to monitor and evaluate urban built environment, gaining insights into complex urban issues and call for social justice.