Physical urban change and its socio-environmental impact: Insights from street view imagery
Abstract
Urban transformation not only reshapes physical spaces but also impacts public perception, influencing how people experience their environments. This study utilizes Street View Imagery (SVI) as an emerging, human-level data source to assess urban changes, providing perspective beyond traditional datasets. Existing studies often focus on either urban physical changes or human perception changes, without bridging the two. This research integrates both aspects by combining a change detection model, trained on a self-labeled dataset, and a human perception model based on the crowdsourced Place Pulse 2.0 dataset with input from 81,630 online volunteers, to analyze urban transformation in New York City and Memphis from 2007 to 2023. Our findings reveal differences between the two cities: New York City exhibited small, isolated changes often driven by community needs, while Memphis transitioned from concentrated to more dispersed development patterns. This study provides insights into how physical changes influence public perception within these two cities. It demonstrates how thoughtful, well-planned urban transformation can improve neighborhoods perception such as safety and livability, while also pointing out potential challenges like gentrification or social fragmentation. These findings provide policymakers with valuable insights into human perception, aiding in the creation of more inclusive, vibrant, and resilient urban transformation. This helps ensure that urban transformation efforts are based on community desires and align with long-term sustainability goals.
Wang Zeyu
Graduate Student
