• DocumentCode
    3294896
  • Title

    Robust estimation of pasture biomass using dual-polarisation TerrASAR-X imagery

  • Author

    McNeill, S.J. ; Pairman, D. ; Belliss, S.E. ; Dalley, D. ; Dynes, R.

  • Author_Institution
    Landcare Res., Christchurch, New Zealand
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    3094
  • Lastpage
    3097
  • Abstract
    The efficient management of pasture is a key driver of profitability for New Zealands pastoral dairy and meat industries. In this paper, we report results from a study that tests the viability of using short-wavelength imaging radar to estimate pasture biomass. We use images from the TerraSAR-X satellite, comparing the HH & HV and VV&HV dual-polarisation combinations. Several linear models have been tested for field-measured pasture biomass. The best model is a linear regression using backscatter from the HH&HV combination, resulting in a residual standard error of 317 kg/ha. This standard error is 61% less than the standard error for the VV&VH combination (511 kg/ha), which clearly suggests adopting the HH&HV model. A model for prediction of the pasture biomass rank percentile is somewhat less convincing than the model for the pasture biomass itself. Finally, a repeated measures analysis for the HH&HV pair, suggests invariance of the regression for pasture biomass over time, except for a possible outlier date 01 September 2008.
  • Keywords
    geophysical image processing; geophysical techniques; synthetic aperture radar; vegetation; New Zealands pastoral dairy industry; TerraSAR-X satellite; dual-polarisation TerraSAR-X imagery; linear regression; meat industry; pasture biomass rank percentile; residual standard error; short-wavelength imaging radar; Biological system modeling; Biomass; Orbits; Predictive models; Radar imaging; Systematics; Pasture biomass; TerraSAR; polarimetry; radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
  • Conference_Location
    Honolulu, HI
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4244-9565-8
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2010.5649266
  • Filename
    5649266