A tale of four cities: Exploring security through environmental characteristics of CCTV equipment placement

Surveillance systems in modern cities are often regarded as the great state panopticon of omnipresent cameras. Drawing on institutional sociology and organizational studies, this article explores urban security through the lens of security projects—strategies or infrastructures which individuals or groups employ to enhance security. Here we challenge the surveillance-centric view by empirically analyzing the environmental conditions of CCTV equipment in four European capitals: Moscow, Paris, Brussels, and Edinburgh, with a focus on understanding their distinct city security projects. We adopt a species distribution modeling approach, treating the cameras as occupying their own “environmental niche” within the urban landscape. We gather locations of CCTV equipment installed in public places by city officials and train a machine learner (CatBoost) to predict camera presence given the urban morphology. The results are interpreted using Interpretable Machine Learning methods (SHapley Additive exPlanations or SHAP) to account for complex and non-linear relationships between types of places. Moscow’s approach features centralized cameras near symbolic landmarks, while Paris and Brussels prioritize network-oriented logic with less emphasis on symbolic spaces. Moreover, certain areas in Brussels fall outside the urban security jurisdiction. Our results offer novel insights into security and urban policy dynamics, contributing to social security studies, sociological institutionalism, and urban policy literature.