• DocumentCode
    576396
  • Title

    Estimating impervious surface of Bohai ring megalopolis from Landsat imagery using SVM method

  • Author

    Sun Zhongchang ; Guo Huadong ; Li Xinwu ; Yang Huaining

  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    7537
  • Lastpage
    7540
  • Abstract
    The objective of this paper is to map large-area impervious surfaces in bohai ring megalopolis areas from Landsat imagery using SVM method. Then, combined with the sixth population census data, the map of the impervious surface area (ISA) per person is derived. Finally, this paper analyses the relationship between the impervious surfaces and population census data, and gross domestic product (GDP) data. Our results indicated that the density of ISA in Beijing and Tianjin were great higher than in other administrative regions. By comparing the ISA with population census and GDP data, our results also indicated that the ISA was highly correlated with population census and GDP data. A strong relationship (R2= 0.879) was observed between the ISA and the population census data in the whole study area. In addition, a strong and positive relationship was observed between the ISA and GDP data (correlation coefficient R2= 0.779 for the whole study area). This research can provide a simple method for policy makers to assess potential urbanization impacts of future urban planning and development activities.
  • Keywords
    demography; economic indicators; geophysical image processing; government policies; support vector machines; terrain mapping; town and country planning; Beijing; Bohai ring megalopolis area; China; GDP data; ISA density; Landsat imagery; SVM method; Tianjin; administrative region; gross domestic product; impervious surface estimation; large-area impervious surface mapping; policy making; potential urbanization impact assessment; sixth population census data; urban development activity; urban planning; Earth; Economic indicators; Remote sensing; Satellites; Sociology; Statistics; Urban areas; GDP data; Landsat TM image; impervious surfaces; support vector machine; the sixth population census data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6351887
  • Filename
    6351887