Eyes on the Streets: Leveraging Street-Level Imaging to Model Urban Crime Dynamics

This study addresses the challenge of urban safety in New York City by examining the relationship between the built environment and crime rates using machine learning and a comprehensive dataset of street view im- ages. We aim to identify how urban landscapes correlate with crime statistics, focusing on the characteristics of street views and their association with crime rates. The findings offer insights for urban planning and crime pre- vention, highlighting the potential of environmental de- sign in enhancing public safety.