Decoding Urban Vitality and Perception with AI
Volume I: Theoretical Foundations and Computational Methods
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Beschreibung
This book delves into the spatial patterns and influencing mechanisms of urban vitality and human perception within the neighborhoods of China's high-density cities, with a specific focus on the Macau Peninsula. Based on a multi-source big data framework integrating Baidu heatmaps, POI, Weibo check-ins, street view imagery, and real estate prices, it quantitatively investigates the spatiotemporal distribution characteristics of block vitality and residents' visual perception. Employing a hybrid computational approach combining GIS spatial analysis, the RAGA-PPM evaluation model, and interpretable machine learning techniques, the book examines the correlation between the built environment and urban vitality, identifies key environmental elements influencing vitality and perception, and discerns the complex pathways through which the built environment affects them. The goal is to provide strategies for the scientific and rational optimization of the built environment in urban planning and design to foster sustainable urban vitality and enhance residents' quality of life.
This book delves into the spatial patterns and influencing mechanisms of urban vitality and human perception within the neighborhoods of China's high-density cities, with a specific focus on the Macau Peninsula. Based on a multi-source big data framework integrating Baidu heatmaps, POI, Weibo check-ins, street view imagery, and real estate prices, it quantitatively investigates the spatiotemporal distribution characteristics of block vitality and residents' visual perception. Employing a hybrid computational approach combining GIS spatial analysis, the RAGA-PPM evaluation model, and interpretable machine learning techniques, the book examines the correlation between the built environment and urban vitality, identifies key environmental elements influencing vitality and perception, and discerns the complex pathways through which the built environment affects them. The goal is to provide strategies for the scientific and rational optimization of the built environment in urban planning and design to foster sustainable urban vitality and enhance residents' quality of life.
Integrates street view imagery and deep learning techniques to analyze both urban vitality and human visual perception Demonstrates the application of quantitative methods, multi-source big data and explainable machine learning models Reveals how the built environment affects neighborhood vitality through visual perception elements
Autor*in
Chen Pan
Themen in »Decoding Urban Vitality and Perception with AI«
Urban vitality Big data in urban planning Neighborhood vitality Spatial analysis Urban study Multi-source data High-density cities Block-scale analysis Sustainable urban development