• DocumentCode
    735469
  • Title

    Spatial pattern recognition of the structure of urban land uses useful for transportation and land use modelling

  • Author

    Beykaei, Seyed Ahad ; Miller, Eric J. ; Zhong, Ming

  • Author_Institution
    IBM Research and Development Centre, IBM Canada 3600 Steeles Ave. East, Markham, Ontario
  • fYear
    2015
  • fDate
    25-28 June 2015
  • Firstpage
    258
  • Lastpage
    263
  • Abstract
    Transportation and land use planners and modelers often use zone systems to take advantage of readily available socio-economic data in their modelling exercises. The most important issue is that analysis zone size is usually large, and therefore, homogeneous or single-type land uses cannot be achieved in many cases. Subsequently, intra-zone travel and mixed activities distribution cannot be captured and modeling accuracy has to be compromised. This study analyzes the form and spatial structure/pattern of different LUs within zone and find correlations between LU types and several morphological properties (building height, building area, building perimeter, building compactness, and parcel area) of parcels and their spatial arrangement indexes (Gabriel Line and Gabriel Length). Binary logistic model is then applied and fitted to the morphological properties and spatial indexes in order to extract residential and commercial LUs. The final Result demonstrates that residential and commercial LUs are extracted with an overall accuracy of 98.4% and 69.0% respectively.
  • Keywords
    Accuracy; Analytical models; Biological system modeling; Buildings; Cities and towns; Computational modeling; Transportation; Land Use Extraction; Land-Use and Transportation Model; Spatial Arrangement Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation Information and Safety (ICTIS), 2015 International Conference on
  • Conference_Location
    Wuhan, China
  • Print_ISBN
    978-1-4799-8693-4
  • Type

    conf

  • DOI
    10.1109/ICTIS.2015.7232117
  • Filename
    7232117