Urban Analytics: History, Trajectory, and Critique

Abstract

Urban analytics combines spatial analysis, statistics, computer science, and urban planning to understand and shape city futures. While it promises better policymaking insights, concerns exist around its epistemological scope and impacts on privacy, ethics, and social control. This chapter reflects on the history and trajectory of urban analytics as a scholarly and professional discipline. In particular, it considers the direction in which this field is going and whether it improves our collective and individual welfare. It first introduces early theories, models, and deductive methods from which the field originated before shifting toward induction. It then explores urban network analytics that enrich traditional representations of spatial interaction and structure. Next it discusses urban applications of spatiotemporal big data and machine learning. Finally, it argues that privacy and ethical concerns are too often ignored as ubiquitous monitoring and analytics can empower social repression. It concludes with a call for a more critical urban analytics that recognizes its epistemological limits, emphasizes human dignity, and learns from and supports marginalized communities.

Keywords: Big Data, Computer Science, Critical Theory, Data Science, Epistemology, Ethics, Geospatial, Machine Learning, Network Science, Physics, Privacy, Simulation, Smart Cities, Spatiotemporal, Statistics, Transportation, Urban Design, Urban Geography, Urban Informatics

JEL Classification: R10, R30, R40