The Invisible City: Not All Streets Are Seen Equally

Abstract

Digital representations of urban streetscapes increasingly depend on street-level panoramic imagery and crowdsourced geospatial data. However, spatial coverage and observation frequency exhibit severe geographic and socio-economic biases. This paper investigates disparities in visual urban observation, demonstrating that marginalized neighborhoods suffer from systematic visual omission in digital twins and urban AI models.

Yunus Serhat Bıçakçı

Assistant Professor

Assistant Professor specializing in GeoAI, Multimodal Vision-Language Models, and Spatial Data Science.