• DocumentCode
    2981147
  • Title

    Derivation of bald earth digital elevation models with X band airborne InSAR

  • Author

    Jiang, Limin ; Xiang, Maosheng

  • Author_Institution
    Anational Key Lab. of Microwave Imaging Technol., Beijing, China
  • fYear
    2009
  • fDate
    26-30 Oct. 2009
  • Firstpage
    800
  • Lastpage
    804
  • Abstract
    Interferometric Synthetic Aperture Radar (InSAR) is a powerful instrument for large scale acquisition of height data for bare earth as well as for vegetated areas and artificial above-ground objects. For many applications, the generation of a bald earth digital elevation model (DEM) is also required. This paper introduces the method of generating a bald earth DEM, referred to as the hierarchical surface fitting technique [7], which operates on the digital surface models (DSM) created using the X band InSAR data provided by the Institute of Electronic, Chinese Academe Sciences. After a short description of the algorithms, the paper presents the results of this technique applied to several DSM data sets, which are accomplished by VC++ program and show that this technique can remove artificial above-ground objects while retaining most of the detail of the original data.
  • Keywords
    airborne radar; digital elevation models; radar interferometry; surface fitting; synthetic aperture radar; Chinese Academe Sciences; DEM; DSM data sets; Institute of Electronic; VC++ program; bald earth digital elevation models; hierarchical surface fitting technique; interferometric synthetic aperture radar; x band airborne InSAR; Data mining; Digital elevation models; Earth; Image generation; Interpolation; Laser radar; Power generation; Surface fitting; Surface topography; Synthetic aperture radar interferometry; DEM; Image Pyramid; InSAR; hierarchical fitting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Synthetic Aperture Radar, 2009. APSAR 2009. 2nd Asian-Pacific Conference on
  • Conference_Location
    Xian, Shanxi
  • Print_ISBN
    978-1-4244-2731-4
  • Electronic_ISBN
    978-1-4244-2732-1
  • Type

    conf

  • DOI
    10.1109/APSAR.2009.5374177
  • Filename
    5374177