09/30: UCGIS Webinar on Urban Visual Intelligence with Dr. Fan Zhang
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Song GAO
Sep 28, 2025, 10:34:21 PMSep 28
to CPG...@listserv.buffalo.edu
Dear Colleagues, Friends, and Students,
Greetings! You are cordially invited to join our incoming UCGIS Webinar on September 30, 2025.
Registration link: https://us02web.zoom.us/webinar/register/WN_LFULFKMJRvGq4lJc3WMCMw
Title: Urban Visual Intelligence: Studying cities with artificial intelligence and street-level imagery
Presenter: Dr. Fan Zhang (Institute of Remote Sensing and GIS, Peking University)
Date and Time: Tuesday, September 30, 12:00pm-1:00pm US Eastern Time
Abstract: Images have played a critical role in the study of how people interact with environments. This presentation reviews the literature of using street-level images (e.g. Google Street View) to understand urban environments. Through a conceptual framework, urban visual intelligence, we systematically discuss new image data sources and AI techniques (e.g. Large Language Model) to (1) observe the urban physical environment via images; (2) derive semantic information from imagery; (3) quantify the physical environment of a place; and (4) understand interactions between physical and socioeconomic environments. These approaches allow researchers to revisit classic urban theories and guide the creation of more human-centric and data-informed urban spaces.
A related paper with open access (free download):
Zhang, F., Salazar-Miranda, A., Duarte, F., Vale, L., Hack, G., Chen, M., Liu, Y., Batty, M., Ratti, C. (2024). Urban Visual Intelligence: Studying cities with artificial intelligence and street-level imagery. Annals of the American Association of Geographers, 114(5), 876–897. https://doi.org/10.1080/24694452.2024.2313515
Bio: Dr. Fan Zhang is an Assistant Professor at the Institute of Remote Sensing and GIS, Peking University. Prior to this, he was a Senior Research Fellow at MIT, where he led the Urban Visual AI group at the MIT Senseable City Lab. His research focuses on geographical artificial intelligence and data-driven urban studies, with particular emphasis on developing urban visual intelligence using street-level imagery. Dr. Zhang's work has been published in journals such as PNAS, Nature Communications, Nature Geoscience, and the Annals of AAG. He currently serves as an Associate Editor for Transactions in Urban Data Science and Technology, and as an Editorial Board Member for the ISPRS Journal of Photogrammetry and Remote Sensing and Computers, Environment and Urban Systems. His notable honors include the CPGIS Young Scholar Award (2024), the Geospatial World 50 Rising Stars Award (2022), and the Global Young Scientist Award in Frontier Science and Technology from WGDC (2020).
See you then!
Song Gao
Communications Director
University Consortium for Geographic Information Science (UCGIS)
Greetings! You are cordially invited to join our incoming UCGIS Webinar on September 30, 2025.
Registration link: https://us02web.zoom.us/webinar/register/WN_LFULFKMJRvGq4lJc3WMCMw
Title: Urban Visual Intelligence: Studying cities with artificial intelligence and street-level imagery
Presenter: Dr. Fan Zhang (Institute of Remote Sensing and GIS, Peking University)
Date and Time: Tuesday, September 30, 12:00pm-1:00pm US Eastern Time
Abstract: Images have played a critical role in the study of how people interact with environments. This presentation reviews the literature of using street-level images (e.g. Google Street View) to understand urban environments. Through a conceptual framework, urban visual intelligence, we systematically discuss new image data sources and AI techniques (e.g. Large Language Model) to (1) observe the urban physical environment via images; (2) derive semantic information from imagery; (3) quantify the physical environment of a place; and (4) understand interactions between physical and socioeconomic environments. These approaches allow researchers to revisit classic urban theories and guide the creation of more human-centric and data-informed urban spaces.
A related paper with open access (free download):
Zhang, F., Salazar-Miranda, A., Duarte, F., Vale, L., Hack, G., Chen, M., Liu, Y., Batty, M., Ratti, C. (2024). Urban Visual Intelligence: Studying cities with artificial intelligence and street-level imagery. Annals of the American Association of Geographers, 114(5), 876–897. https://doi.org/10.1080/24694452.2024.2313515
Bio: Dr. Fan Zhang is an Assistant Professor at the Institute of Remote Sensing and GIS, Peking University. Prior to this, he was a Senior Research Fellow at MIT, where he led the Urban Visual AI group at the MIT Senseable City Lab. His research focuses on geographical artificial intelligence and data-driven urban studies, with particular emphasis on developing urban visual intelligence using street-level imagery. Dr. Zhang's work has been published in journals such as PNAS, Nature Communications, Nature Geoscience, and the Annals of AAG. He currently serves as an Associate Editor for Transactions in Urban Data Science and Technology, and as an Editorial Board Member for the ISPRS Journal of Photogrammetry and Remote Sensing and Computers, Environment and Urban Systems. His notable honors include the CPGIS Young Scholar Award (2024), the Geospatial World 50 Rising Stars Award (2022), and the Global Young Scientist Award in Frontier Science and Technology from WGDC (2020).
See you then!
Song Gao
Communications Director
University Consortium for Geographic Information Science (UCGIS)
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