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Front Cover -- URBAN SYSTEMS DESIGN -- URBAN SYSTEMS DESIGN -- Copyright -- Contents -- Contributors -- Preface -- 1 - Urban systems design: shaping smart cities by integrating urban design and systems science -- 1.1 Cities as flows: emerging new urban forms driven by smart city movement -- 1.1.1 Theories for smart cities -- 1.1.2 Cities as flows: an emerging new urban form -- 1.2 Urban design: designing situational, resilient, and transformative urban spaces -- 1.2.1 Intellectual legacy of urban design as a normative theory -- 1.2.2 Intellectual legacy of urban metabolism movement in Japan -- 1.2.3 Urban spaces are situational, resilient, and transformative in the context of IoT -- 1.3 Systems science: understanding urban complexity and big data -- 1.3.1 Urban complexity and big data -- 1.3.2 Modeling smart urban systems -- 1.4 Urban systems design: four possible models -- 1.4.1 Urban sensing systems as a human interactive model -- 1.4.2 Data-driven urban design as a normative model -- 1.4.3 Urban metabolism as a functional model -- 1.4.4 Geodesign as a procedure model -- References -- 2 - Urban systems and the role of big data -- 2.1 Introduction -- 2.2 Data analytics of urban systems -- 2.2.1 Modeling urban complex system -- 2.2.2 The role of urban data analytics -- 2.2.3 A framework of urban data analytics -- 2.3 IoT as a new smart infrastructure -- 2.3.1 New advancements of complexity models in the IoT era -- 2.3.2 Smart city and ICT infrastructure with vehicle to X applications toward urban decarbonization -- 2.3.3 IoT for modeling and monitoring smart buildings -- 2.3.4 Hands-on technologies for better understanding of urban complexity with big data -- 2.3.5 Integrated planning support systems with big data and AI -- 2.4 Smart objects in urban systems design -- 2.4.1 Implementing smart buildings.

Previously, GIS-based visibility analysis has been conducted mainly in two dimensions, based on the concept of an isovist in the built environment or the concept of a viewshed in terrain and landscape analysis. The Viewsphere, a GIS approach towards 3D visibility analysis is proposed for measuring visible urban space quantitatively in a way that is different from its predecessors, the isovist and the viewshed. A test case of Singapore's urban space was conducted by evaluating the visibility of three alternative urban design scenarios and their potential impacts on the visual quality of open space. Both directional and nondirectional approaches were applied to the mapping of visibility based on the 2D and 3D indices. The proposition that 3D visibility indices are more effective than 2D indices was verified. The findings show that the 3D indices are sensitive to the changes of z-dimension.