• DocumentCode
    2879550
  • Title

    Monitoring on Urban Spatial Expansion Based on CBERS Images

  • Author

    Wang, Huaibao ; Zhao, He

  • Author_Institution
    Sch. of Geomatics & Prospecting Eng., Jilin Inst. of Archit. & Civil Eng., Changchun, China
  • fYear
    2012
  • fDate
    1-3 June 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Using remote sensing technology to monitor urban growth has become a trend. Various remote sensing data were engaged in monitoring the spatial and temporal processes of urban expansion and land use change. The CBERS has been applied in many fields. Based on multi-temporal CBERS imageries, the research extracted the urban built-up areas in Changchun city, Jilin province, China, on the basis of supervised classification method, Maximum Likelihood classifier. Overlay and buffer spatial analysis was used to study urban growth direction. At last, the major drive forces behind urban expansion were analyzed by using socio-economic statistics. This research has verified the applicability of urban growth monitoring based on CBERS imageries, and then, should enrich urban expansion data source and extend the CBERS application field.
  • Keywords
    geophysical image processing; image classification; land use planning; maximum likelihood estimation; socio-economic effects; spatiotemporal phenomena; terrain mapping; CBERS image; China; buffer spatial analysis; maximum likelihood classifier; overlay analysis; remote sensing technology; socioeconomic statistics; spatial process; supervised classification method; temporal process; urban built-up area; urban growth monitoring; Cities and towns; Economics; Entropy; Monitoring; Remote sensing; Satellites; Urban areas;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0872-4
  • Type

    conf

  • DOI
    10.1109/RSETE.2012.6260632
  • Filename
    6260632