• DocumentCode
    143665
  • Title

    Object based building extraction by QuickBird image for population estimation: A case study of the City of Waterloo

  • Author

    Wei Li ; Shiqian Wang ; Li, Jonathan

  • Author_Institution
    Dept. of Geogr. & Environ. Manage., Univ. of Waterloo, Waterloo, ON, Canada
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    3176
  • Lastpage
    3179
  • Abstract
    This paper used QuickBird high resolution image to estimate the population of the city of Waterloo, ON, Canada. Two approaches of object based classification were compared to extract buildings from the original image. One is rule based classification and the other is example based classification. We chose two districts which are Lakeshore and Columbia as our testing areas. Rule based result is better than example based. The overall accuracy of rule based classification in Lakeshore District and Columbia District are 92.5% and 85.5%. With census data, the average area per person is about 38.8 m2 and the estimated population of the city of Waterloo is about 109589.
  • Keywords
    buildings (structures); feature extraction; geophysical image processing; image classification; image resolution; knowledge based systems; Canada; Columbia district; Lakeshore district; ON; QuickBird high resolution image; Waterloo city; building extraction; object based building extraction; object based classification; population estimation; rule based method; Accuracy; Buildings; Cities and towns; Estimation; Remote sensing; Sociology; Statistics; QuickBird; high resolution; object-based classification; population estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6947152
  • Filename
    6947152