• DocumentCode
    2990634
  • Title

    Building-based urban land use classification from vector databases in Manchester, UK

  • Author

    Hussain, Masroor ; Barr, Robet ; Chen, Dongmei

  • Author_Institution
    Dept. of Geogr., Queen´´s Univ., Kingston, ON, Canada
  • fYear
    2012
  • fDate
    15-17 June 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    The recognition, analysis and classification of urban structures are important in urban land use modeling. The form and the function of individual urban elements such as buildings and street blocks help us better understand the urban morphology. The types, layout and arrangement of these buildings form up the local characteristics of urban areas. A model has been developed to classify urban areas based on the cartometric properties of buildings and the patterns they make. Supervised and un-supervised classification algorithms from data mining techniques along with GIS are explored to help create a framework for extracting information from vector databases and classifying building and blocks. The methodology is developed and applied to Manchester metropolitan in the UK.
  • Keywords
    data mining; geographic information systems; information retrieval; land use planning; pattern classification; terrain mapping; visual databases; GIS; Manchester; UK; building blocks; building cartometric properties; building-based urban land use classification; information extraction framework; street blocks; supervised classification algorithm; unsupervised classification algorithm; urban area local characteristics; urban land use model; urban structure analysis; urban structure classification; urban structure recognition; vector databases; Buildings; Data Mining; Decision Tree; Geographic Information System (GIS); Structural Classification; Urban Areas;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-4673-1103-8
  • Type

    conf

  • DOI
    10.1109/Geoinformatics.2012.6270327
  • Filename
    6270327