• DocumentCode
    3349124
  • Title

    Estimation of vegetation parameters from MODIS FPAR time series, Landsat TM and ETM+ products, and ICESat for soil erosion modelling

  • Author

    Schoettker, Birte ; Scarth, Peter ; Phinn, Stuart ; Denham, Robert ; Schmidt, Michael

  • Author_Institution
    Centre for Spatial Environ. Res. (CSER), Univ. of Queensland, Brisbane, QLD, Australia
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    2083
  • Lastpage
    2086
  • Abstract
    This study builds on results from our analysis of a time series of the global MODIS Fraction of Absorbed Photosynthetically Active radiation that a plant canopy absorbs, and a relationship between the product to Landsat TM and ETM+ green and non-green fractions of ground cover and vegetation structural categories in the dry tropical savannas in Queensland, Australia. In a multiple regression analysis (including interaction terms) 75% of the variability in dry season MODIS FPAR was explained by the Landsat datasets. The vegetation structural categories were determined through classes of Landsat woody foliage projective cover. Based on those findings, we developed three schemes to derive high temporal, remotely sensed cover factor estimates integrating the MODIS FPAR with the Landsat products, and ICESat canopy height estimates for potential use in future erosion modelling. Those cover factor schemes are the first of their kind, and a future study will enable their validation.
  • Keywords
    erosion; geophysical techniques; radiometry; time series; vegetation; Australia; ETM+ products; ICESat canopy height estimates; LANDSAT TM data; Landsat datasets; MODIS FPAR time series; Queensland; multiple regression analysis; soil erosion modelling; vegetation parameters; Earth; MODIS; Mathematical model; Remote sensing; Satellites; Time series analysis; Vegetation mapping; ETM+; ICESat; Landsat TM; MODIS FPAR; cover factor; vegetation structure;
  • 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.2010.5652372
  • Filename
    5652372