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Semantic urban modelling: Knowledge representation of urban space

Author

Listed:
  • Mauro Berta
  • Luca Caneparo
  • Alfonso Montuori
  • Davide Rolfo

Abstract

The paper presents a methodology for describing in generative terms the structure of urban fabrics: the objective is to transfer conceptually the knowledge about the domain of urban space into a hierarchical and interrelated semantic structure with relevant concepts, elements and their mutual relationships, providing explicit and unambiguous definitions. The conceptual and operational instrument adopted for this purpose is the ontology, a method of knowledge representation and management coming from the Artificial Intelligence. This approach aims to create a customisable digital design tool, to support the designer in the early stages of urban design process, such as street pattern and massing definition, by generating in real time a number of design scenarios, starting from a large number of constraints and requests. This paper focuses on the knowledge formalisation aspects of the research that is the basis for the generative modelling of urban space.

Suggested Citation

  • Mauro Berta & Luca Caneparo & Alfonso Montuori & Davide Rolfo, 2016. "Semantic urban modelling: Knowledge representation of urban space," Environment and Planning B, , vol. 43(4), pages 610-639, July.
  • Handle: RePEc:sae:envirb:v:43:y:2016:i:4:p:610-639
    DOI: 10.1177/0265813515609820
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    References listed on IDEAS

    as
    1. Kristian Kloeckl & Oliver Senn & Carlo Ratti, 2012. "Enabling the Real-Time City: LIVE Singapore!," Journal of Urban Technology, Taylor & Francis Journals, vol. 19(2), pages 89-112.
    2. Christine Chan & Simon Suigen Guo & Robert Harrison, 2011. "Decision Support Tools for Ontological Engineering," Chapters, in: Chiang Jao (ed.), Efficient Decision Support Systems - Practice and Challenges From Current to Future, IntechOpen.
    Full references (including those not matched with items on IDEAS)

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