• DocumentCode
    3071678
  • Title

    Building extraction using lidar data and very high resolution image over complex urban area

  • Author

    Peijun Li ; Shasha Jiang ; Xue Wang ; Jun Zhang

  • Author_Institution
    Inst. of Remote Sensing & GIS, Peking Univ., Beijing, China
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    4253
  • Lastpage
    4256
  • Abstract
    This paper proposed a novel urban building extraction method to address the problems with shadow and spectral confusion using LiDAR data and very high resolution (VHR) imagery. The buildings were first extracted using height from LiDAR data and normalized difference vegetation index (NDVI) from VHR image. A refinement step was then adopted to reduce the errors caused by shadow and spectral similarity between the buildings with color roofs and vegetated roofs and the trees. A post processing step was finally conducted to further improve the result. The proposed method was quantitatively evaluated and compared with existing method using airborne LiDAR data and Quickbird image. The results indicated that the proposed method significantly outperformed the existing method. The proposed method is applicable for building extraction using VHR image and LiDAR data over complex urban areas with tall buildings and buildings with color roofs or vegetated roofs.
  • Keywords
    feature extraction; geophysical image processing; image resolution; image segmentation; remote sensing by laser beam; vegetation mapping; LiDAR data; Quickbird image; complex urban areas; normalized difference vegetation index; post processing method; refinement method; shadow; spectral confusion; urban building extraction method; very high resolution imagery; Accuracy; Buildings; Data mining; Image segmentation; Laser radar; Urban areas; Vegetation; LiDAR; VHR image; building extraction; shadow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
  • Conference_Location
    Melbourne, VIC
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4799-1114-1
  • Type

    conf

  • DOI
    10.1109/IGARSS.2013.6723773
  • Filename
    6723773