• DocumentCode
    2711143
  • Title

    Measuring neighbourhood sustainability performance: An indexing model for Gold Coast City, Australia

  • Author

    Dur, Fatih ; Yigitcanlar, Tan ; Bunker, Jonathan

  • Author_Institution
    Sch. of Urban Dev., Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The aim of this research is to develop an indexing model to evaluate sustainability performance of urban settings, in order to assess environmental impacts of urban development and to provide planning agencies an indexing model as a decision support tool to be used in curbing negative impacts of urban development. Indicator-based sustainability assessment is embraced as the method. Neighbourhood-level urban form and transport related indicators are derived from the literature by conducting a content analysis and finalised via a focus group meeting. The model is piloted on three suburbs of Gold Coast City, Australia. Final neighbourhood level sustainability index score was calculated by employing equal weighting schema. The results of the study show that indexing modelling is a reasonably practical method to measure and visualise local sustainability performance, which can be employed as an effective communication and decision making tool.
  • Keywords
    decision support systems; indexing; sustainable development; town and country planning; Australia; Gold Coast City; content analysis; decision support tool; indexing model; indicator-based sustainability assessment; planning agencies; urban development; urban settings; Cities and towns; Geographic Information Systems; Gold; Indexing; Local government; Planning; Geographic Information System (GIS); composite indicators; planning decision support system; spatial indexing; sustainable urban development;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980983
  • Filename
    5980983