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A Semantic Spatial Policy Model to Automatically Calculate Allowable Gross Floor Areas in Singapore

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Computer-Aided Architectural Design. INTERCONNECTIONS: Co-computing Beyond Boundaries (CAAD Futures 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1819))

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Abstract

Urban data analytics is helping to shape current and future cities, but the process of generating urban analytical indicators is often difficult to scale and automate. For instance, planners determine allowable Gross Floor Area (GFA) on a plot by manually cross-referencing multi-domain policies. As allowable GFA governs potential future developments, it is imperative to quantify and understand its values city-wide.

This paper presents the first steps of a research effort to develop an automated semantic spatial policy model to estimate allowable GFA for plots in Singapore. We use ontologies and Knowledge Graph (KG) platforms to address regulatory data interoperability and automation challenges. We filtered regulation concepts that determine buildable area and volume at Level of Detail 1 (LoD1) and standardised these concepts across different regulatory sources. Then, we modelled concept-related policies and automated the generation of possible GFA values per plot. Finally, we developed an ontology to store these values in a dynamic geospatial KG. Our approach presents two key benefits: 1) a generated dataset of allowable GFA eliminates the need for manual calculation by field experts, and 2) a graph data structure is ideally suited for unstructured regulatory data, like planning regulations.

We conclude that semantic spatial policy models improve the interoperability between multi-domain regulatory data and plan to generate a dataset for the entire Singapore as well as integrate regulatory data for mixed-use plots.

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Authors and Affiliations

  1. Singapore-ETH Centre, Future Cities Lab Global Programme, CREATE Campus, 1 CREATE Way, #06-01 CREATE Tower, Singapore, 138602, Singapore

    Ayda Grisiute, Heidi Silvennoinen, Shiying Li & Pieter Herthogs

  2. CARES, Cambridge Centre for Advanced Research and Education in Singapore, Singapore, Singapore

    Arkadiusz Chadzynski & Markus Kraft

  3. Institute of Cartography and Geoinformation, ETH Zurich, Zurich, Switzerland

    Ayda Grisiute & Martin Raubal

  4. Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK

    Markus Kraft

  5. School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore, 637459, Singapore

    Markus Kraft

  6. The Alan Turing Institute, London, UK

    Markus Kraft

  7. Arup, Berlin, Germany

    Aurel von Richthofen

Authors
  1. Ayda Grisiute
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  2. Heidi Silvennoinen
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  3. Shiying Li
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  4. Arkadiusz Chadzynski
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  5. Martin Raubal
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  7. Aurel von Richthofen
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  8. Pieter Herthogs
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Corresponding author

Correspondence to Ayda Grisiute .

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Editors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    Michela Turrin

  2. Delft University of Technology, Delft, The Netherlands

    Charalampos Andriotis

  3. Delft University of Technology, Delft, The Netherlands

    Azarakhsh Rafiee

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Grisiute, A. et al. (2023). A Semantic Spatial Policy Model to Automatically Calculate Allowable Gross Floor Areas in Singapore. In: Turrin, M., Andriotis, C., Rafiee, A. (eds) Computer-Aided Architectural Design. INTERCONNECTIONS: Co-computing Beyond Boundaries. CAAD Futures 2023. Communications in Computer and Information Science, vol 1819. Springer, Cham. https://doi.org/10.1007/978-3-031-37189-9_30

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  • DOI: https://doi.org/10.1007/978-3-031-37189-9_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37188-2

  • Online ISBN: 978-3-031-37189-9

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