Street View Imagery: Have We Answered All The Questions With It? What’s Left to Do?

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Abstract

Join us in an exploration of the untapped potential in Street View Imagery (SVI) within the realm of spatial data science.

Date
Sep 6, 2023 12:45 PM
Location
Online

Session Format:

A Series of Presentations

Session Description:

Join us in an engaging exploration of the untapped potential in Street View Imagery (SVI) within the realm of spatial data science. As we continue to witness remarkable advancements, there lingers the question: Have we exhausted all SVI possibilities or are there uncharted territories waiting to be discovered? With the emergence of breakthrough technologies such as large language models, generative AI methods, and graph-based learning, we believe there is an abundant opportunity to leverage SVI across multiple urban domains.

In this thought-provoking session, we bridge the gap between experienced researchers and newcomers to SVI by showcasing an array of innovative work and encouraging stimulating discussions around prevailing challenges and future research possibilities. The presentations will cover:

  • Unleashing creativity in identifying novel research topics
  • Advancing methodological approaches for SVI
  • Overcoming limitations and exploring complementary techniques
  • Navigating potential barriers and fostering a supportive environment for new researchers
  • Linking SVI approaches to socio-economic perceptions of the city

Session Hosts

Guest Speakers

  • Mohamed R. Ibrahim: Lecturer (Assistant Professor) in Spatial Data Science, University of Leeds
  • Yuhao Kang: Assistant Professor at the University of South Carolina
  • Pengyuan Liu: Assistant Professor at Nanjing University of Information Science and Technology

Target Audience

Our session is designed to engage a broad spectrum of attendees. From seasoned SVI researchers and novices to city planners and urban practitioners who utilize SVI surveybased methods to gain urban context insights. By featuring our esteemed guest speakers, each a torchbearer in SVI expertise and experience, we aspire to kindle interest, promote innovation, and foster a collaborative environment for all participants. Join us in this quest to redefine the boundaries of SVI and unearth the possibilities together.

Koichi Ito
Koichi Ito
PhD Candidate in Urban Analytics at the National University of Singapore

My research interests include urban analytics, spatial analysis and human mobility.

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