• DocumentCode
    2714171
  • Title

    Assessment of waterlogging hazard in Tianhe District of Guangzhou City using remote sensing and GIS

  • Author

    Huang, Tielan ; Wang, Yunpeng

  • Author_Institution
    Guangzhou Inst. of Geochem., Chinese Acad. of Sci., Guangzhou, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In recent years, as expansion of city size and urban population, waterlogging has become more frequently in Guangzhou. It has seriously affected people´s routine life. In this study, an urban waterlogging model based on SCS (Soil Conservation Service) model and the GIS was built and was applied to assess hazard risk of waterlogging in Tianhe District of Guangzhou, China. It consists of three parts: urban terrain model, urban rainfall-runoff model and GIS spatial analysis model. Rainfall data of most frequent rainstorms in 2010 of Tianhe District were used in our model to assess the risk of waterlogging hazard. Our results show that the risky areas are almost located in southern region of Tianhe District, where located most of commercial and residential populations. Some risky areas are located in central region and few risky areas are located in the northern region. The modeling results consist with the reported real situation, which validated our methods.
  • Keywords
    disasters; geographic information systems; hazards; hydrological techniques; rain; terrain mapping; China; GIS spatial analysis model; Guangzhou City; Tianhe District; geographic information system; rainfall data; remote sensing; urban rainfall-runoff model; urban terrain model; waterlogging hazard; Analytical models; Cities and towns; Data models; Floods; Geographic Information Systems; Vegetation mapping; GIS; Tianhe District of Guangzhou; remote sensing; urban waterlogging model; waterlogging hazard assessment;
  • 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.2011.5981159
  • Filename
    5981159