Martina Mazzarello – författare

In an era where extreme amounts of data are produced daily, with the majority being visual content, cities have become vast repositories of digital imagery. From surveillance cameras to smartphone photos, satellite imagery to street-level captures, our urban environments are continuously documented through an unprecedented volume of visual data. This groundbreaking book examines how artificial intelligence (AI) is revolutionizing our understanding of cities and presents a comprehensive framework for applying visual AI in urban contexts. The book traces the evolution of visual analysis in urban studies, from early photographic documentation to today's sophisticated AI-powered interpretations. Through detailed case studies from across the United States, Stockholm, Amsterdam, Beijing, Dubai, Singapore, and more, it demonstrates how machine learning is unveiling new insights about urban patterns, human behavior, and social dynamics in cities. Chapters address critical concerns about surveillance, privacy, and algorithmic bias, offering a nuanced perspective on the ethical implications of urban visual intelligence. This book is essential for scholars and postgraduate students in urban planning and landscape architecture, while also appealing to anyone interested in the future of cities and technology's role in understanding them.

In an era where extreme amounts of data are produced daily, with the majority being visual content, cities have become vast repositories of digital imagery. From surveillance cameras to smartphone photos, satellite imagery to street-level captures, our urban environments are continuously documented through an unprecedented volume of visual data. This groundbreaking book examines how artificial intelligence (AI) is revolutionizing our understanding of cities and presents a comprehensive framework for applying visual AI in urban contexts. The book traces the evolution of visual analysis in urban studies, from early photographic documentation to today’s sophisticated AI-powered interpretations. Through detailed case studies from across the United States, Stockholm, Amsterdam, Beijing, Dubai, Singapore, and more, it demonstrates how machine learning is unveiling new insights about urban patterns, human behavior, and social dynamics in cities. Chapters address critical concerns about surveillance, privacy, and algorithmic bias, offering a nuanced perspective on the ethical implications of urban visual intelligence. This book is essential for scholars and postgraduate students in urban planning and landscape architecture, while also appealing to anyone interested in the future of cities and technology’s role in understanding them.