In the present chapter, we discuss the graph representations of urban spatial patterns (maps) and suggest a computationally feasible technique for understanding urban forms based on scale-dependent random walks that can be used in order to spot the relatively isolated locations and neighborhoods, to detect urban sprawl, and to illuminate the hidden community structures in complex urban textures. The approach may be implemented for the detailed expertise of any urban pattern and the associated transport networks that may include many transportation modes.
Research Professor. Director at Learning Change Project – Research on society, culture, art, neuroscience, cognition, critical thinking, intelligence, creativity, autopoiesis, self-organization, rhizomes, complexity, systems, networks, leadership, sustainability, thinkers, futures ++
Giorgio Bertini does not work for, consult, own shares in or receive funding from any company or organization that would benefit from these papers, and has disclosed no relevant affiliations beyond their academic appointment.
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