• DocumentCode
    576598
  • Title

    A new three-stage inversion procedure of forest height with the Improved Temporal Decorrelation RVoG model

  • Author

    Li, Zhen ; Guo, Ming

  • Author_Institution
    Center for Earth Obs. & Digital Earth, Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    5141
  • Lastpage
    5144
  • Abstract
    Forest parameters can be estimated using the single baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data using the Random Volume over ground (RVoG) model. For a long-term temporal baseline, temporal decorrelation was present in all the polarimetric channels for the entire range of the synthetic aperture radar (SAR) data due to the complex changes process of the two temporal acquisitions. To overcome this problem, the Improved Temporal Decorrelation Random Volume over Ground (Improved TD-RVoG) model, based on the RVoG model is developed to minimise the effect of temporal decorrelation. This model introduces a new temporal decorrelation function requiring only one more additional parameter than the RVoG model. The new model is appropriate for use with the `Three stage inversion´ procedure. Finally, the new model is validated by using single-baseline Advanced Land Observing Satellite (ALOS) SAR data.
  • Keywords
    synthetic aperture radar; vegetation; ALOS SAR data; PolInSAR data; Temporal Decorrelation Random Volume over Ground; complex changes process; forest height; forest parameters; improved TD-RVoG model; single baseline polarimetric synthetic aperture radar interferometry; single-baseline Advanced Land Observing Satellite; temporal acquisitions; temporal decorrelation RVoG model; three-stage inversion procedure; Brain modeling; Coherence; Decorrelation; Equations; Mathematical model; Solid modeling; Standards; ALOS/PALSAR; Forest Height; PolInSAR; Temporal Decorrelation;
  • 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.2012.6352453
  • Filename
    6352453